Ceros provides tools and services that empower companies to create interactive content with unparalleled ease and efficiency, driving customer engagement to new levels.

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This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Jakob Vogel, M.A. Digital Humanities, Institute for Digital Humanities, Faculty of Philosophy, Georg August University of G¨ottingen. Table of Links Abstract and Intro
Diverse cross-document coreference and media bias analysis
Annotation tool
Annotation guidelines
Conclusion and future work
Acknowledgements
Bibliographical References 7. Bibliographical References Ad Fontes Media, Inc. 2023. Media Bias Chart, Version 2.8.4. https://adfontesmedia.com/interactive-mediabias-chart/, accessed 06 Jul 2023. AllSides Technologies Inc. 2023. AllSides Media Bias Chart, Version 9.0. https://www.allsides.com/media-bias/mediabias-chart, accessed 06 Jul 2023. Herbert H. Clark and Adrian Bangerter. 2004. Changing ideas about reference. In Experimental pragmatics, pages 25–49. Springer. Herbert H. Clark and Susan E Haviland. 1977. Comprehension and the Given-New contract. In Discourse Production and Comprehension, pages 1–40. Erlbaum. Felix Hamborg, Anastasia Zhukova, and Bela Gipp. 2019. Automated identification of media bias by word choice and labeling in news articles. In 2019 ACM/IEEE Joint Conference on Digital Libraries (JCDL), pages 196–205. IEEE. Lynette Hirschman and Nancy Chinchor. 1998. Appendix F: MUC-7 coreference task definition (version 3.0). In Seventh Message Understanding Conference (MUC-7): Proceedings of a Conference Held in Fairfax, Virginia, April 29-May 1, 1998. Jan-Christoph Klie, Michael Bugert, Beto Boullosa, Richard Eckart de Castilho, and Iryna Gurevych. 2018. The INCEpTION Platform: Machine-Assisted and Knowledge-Oriented Interactive Annotation. In Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations, pages 5–9. Association for Computational Linguistics. Royce Kurmelovs. 2023. Fox News labels Joe Biden a ’wannabe dictator’ during Trump speech. The Guardian. https://www.theguardian.com/media/2023/jun/14/foxnews-labels-joe-biden-a-wannabe-dictatorduring-trump-speech, accessed 13 Sep 2023. Linguistic Data Consortium. 2005. ACE (Automatic Content Extraction) English Annotation Guidelines for Events, Version 5.4.3. https://www.ldc.upenn.edu/sites/www.ldc.upenn .edu/files/english-events-guidelines-v5.4.3.pdf, accessed 22 Sep 2023. Linguistic Data Consortium. 2008. ACE (Automatic Content Extraction) English Annotation Guidelines for Entities, Version 6.6. https://www.ldc.upenn.edu/sites/www.ldc.upenn .edu/files/english-entities-guidelines-v6.6.pdf, accessed 18 Sep 2023. Ruicheng Liu, Rui Mao, Anh Tuan Luu, and Erik Cambria. 2023. A brief survey on recent advances in coreference resolution. Artificial Intelligence Review, pages 1–43. Michael Luciano. 2023. Trump Debuts New Nickname for Biden at New Hampshire Rally. Mediaite. https://www.mediaite.com/politics/trumpdebuts-new-nickname-for-biden-at-newhampshire-rally/, accessed 13 Sep 2023. Anna Nedoluzhko, Jiˇr´ı M´ırovsk`y, and Petr Pajas. 2009. The coding scheme for annotating extended nominal coreference and bridging anaphora in the Prague Dependency Treebank. In Proceedings of the Third Linguistic Annotation Workshop (LAW III), pages 108–111. Tim O’Gorman, Kristin Wright-Bettner, and Martha Palmer. 2016. Richer event description: Integrating event coreference with temporal, causal and bridging annotation. In Proceedings of the 2nd workshop on computing news storylines (CNS 2016), pages 47–56. Marta Recasens, Eduard Hovy, and M. Ant`onia Mart´ı. 2010. A Typology of Near-Identity Relations for Coreference (NIDENT). In Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC’10), Valletta, Malta. European Language Resources Association (ELRA). Sasha Spala, Nicholas A Miller, Yiming Yang, Franck Dernoncourt, and Carl Dockhorn. 2019. DEFT: A corpus for definition extraction in free-and semi-structured text. In Proceedings of the 13th Linguistic Annotation Workshop, pages 124–131. Timo Spinde, Christina Kreuter, Wolfgang Gaissmaier, Felix Hamborg, Bela Gipp, and Helge Giese. 2021a. Do you think it’s biased? how to ask for the perception of media bias. In 2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL), pages 61–69. IEEE. Timo Spinde, David Krieger, Manuel Plank, and Bela Gipp. 2021b. Towards a reliable groundtruth for biased language detection. In 2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL), pages 324–325. IEEE. Anastasia Zhukova, Felix Hamborg, Karsten Donnay, and Bela Gipp. 2022. XCoref: Crossdocument coreference resolution in the wild. In International Conference on Information, pages 272–291. Springer. Anastasia Zhukova, Felix Hamborg, and Bela Gipp. 2021. Towards Evaluation of Crossdocument Coreference Resolution Models Using Datasets with Diverse Annotation Schemes. arXiv preprint arXiv:2109.05250. This paper is available on arxiv under CC 4.0 license. Authors: (1) Jakob Vogel, M.A. Digital Humanities, Institute for Digital Humanities, Faculty of Philosophy, Georg August University of G¨ottingen. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Jakob Vogel, M.A. Digital Humanities, Institute for Digital Humanities, Faculty of Philosophy, Georg August University of G¨ottingen. Table of Links Abstract and Intro Diverse cross-document coreference and media bias analysis Annotation tool Annotation guidelines Conclusion and future work Acknowledgements Bibliographical References Abstract and Intro Abstract and Intro Diverse cross-document coreference and media bias analysis Diverse cross-document coreference and media bias analysis Annotation tool Annotation tool Annotation guidelines Annotation guidelines Conclusion and future work Conclusion and future work Acknowledgements Acknowledgements Bibliographical References Bibliographical References 7. Bibliographical References Ad Fontes Media, Inc. 2023. Media Bias Chart, Version 2.8.4. https://adfontesmedia.com/interactive-mediabias-chart/, accessed 06 Jul 2023. AllSides Technologies Inc. 2023. AllSides Media Bias Chart, Version 9.0. https://www.allsides.com/media-bias/mediabias-chart, accessed 06 Jul 2023. Herbert H. Clark and Adrian Bangerter. 2004. Changing ideas about reference. In Experimental pragmatics, pages 25–49. Springer. Herbert H. Clark and Susan E Haviland. 1977. Comprehension and the Given-New contract. In Discourse Production and Comprehension, pages 1–40. Erlbaum. Felix Hamborg, Anastasia Zhukova, and Bela Gipp. 2019. Automated identification of media bias by word choice and labeling in news articles. In 2019 ACM/IEEE Joint Conference on Digital Libraries (JCDL), pages 196–205. IEEE. Lynette Hirschman and Nancy Chinchor. 1998. Appendix F: MUC-7 coreference task definition (version 3.0). In Seventh Message Understanding Conference (MUC-7): Proceedings of a Conference Held in Fairfax, Virginia, April 29-May 1, 1998. Jan-Christoph Klie, Michael Bugert, Beto Boullosa, Richard Eckart de Castilho, and Iryna Gurevych. 2018. The INCEpTION Platform: Machine-Assisted and Knowledge-Oriented Interactive Annotation. In Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations, pages 5–9. Association for Computational Linguistics. Royce Kurmelovs. 2023. Fox News labels Joe Biden a ’wannabe dictator’ during Trump speech. The Guardian. https://www.theguardian.com/media/2023/jun/14/foxnews-labels-joe-biden-a-wannabe-dictatorduring-trump-speech, accessed 13 Sep 2023. Linguistic Data Consortium. 2005. ACE (Automatic Content Extraction) English Annotation Guidelines for Events, Version 5.4.3. https://www.ldc.upenn.edu/sites/www.ldc.upenn .edu/files/english-events-guidelines-v5.4.3.pdf, accessed 22 Sep 2023. Linguistic Data Consortium. 2008. ACE (Automatic Content Extraction) English Annotation Guidelines for Entities, Version 6.6. https://www.ldc.upenn.edu/sites/www.ldc.upenn .edu/files/english-entities-guidelines-v6.6.pdf, accessed 18 Sep 2023. Ruicheng Liu, Rui Mao, Anh Tuan Luu, and Erik Cambria. 2023. A brief survey on recent advances in coreference resolution. Artificial Intelligence Review, pages 1–43. Michael Luciano. 2023. Trump Debuts New Nickname for Biden at New Hampshire Rally. Mediaite. https://www.mediaite.com/politics/trumpdebuts-new-nickname-for-biden-at-newhampshire-rally/, accessed 13 Sep 2023. Anna Nedoluzhko, Jiˇr´ı M´ırovsk`y, and Petr Pajas. 2009. The coding scheme for annotating extended nominal coreference and bridging anaphora in the Prague Dependency Treebank. In Proceedings of the Third Linguistic Annotation Workshop (LAW III), pages 108–111. Tim O’Gorman, Kristin Wright-Bettner, and Martha Palmer. 2016. Richer event description: Integrating event coreference with temporal, causal and bridging annotation. In Proceedings of the 2nd workshop on computing news storylines (CNS 2016), pages 47–56. Marta Recasens, Eduard Hovy, and M. Ant`onia Mart´ı. 2010. A Typology of Near-Identity Relations for Coreference (NIDENT). In Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC’10), Valletta, Malta. European Language Resources Association (ELRA). Sasha Spala, Nicholas A Miller, Yiming Yang, Franck Dernoncourt, and Carl Dockhorn. 2019. DEFT: A corpus for definition extraction in free-and semi-structured text. In Proceedings of the 13th Linguistic Annotation Workshop, pages 124–131. Timo Spinde, Christina Kreuter, Wolfgang Gaissmaier, Felix Hamborg, Bela Gipp, and Helge Giese. 2021a. Do you think it’s biased? how to ask for the perception of media bias. In 2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL), pages 61–69. IEEE. Timo Spinde, David Krieger, Manuel Plank, and Bela Gipp. 2021b. Towards a reliable groundtruth for biased language detection. In 2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL), pages 324–325. IEEE. Anastasia Zhukova, Felix Hamborg, Karsten Donnay, and Bela Gipp. 2022. XCoref: Crossdocument coreference resolution in the wild. In International Conference on Information, pages 272–291. Springer. Anastasia Zhukova, Felix Hamborg, and Bela Gipp. 2021. Towards Evaluation of Crossdocument Coreference Resolution Models Using Datasets with Diverse Annotation Schemes. arXiv preprint arXiv:2109.05250.

Code Book for Annotation of Diverse Cross-Document Coreference: Conclusion and Future Work

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Jakob Vogel, M.A. Digital Humanities, Institute for Digital Humanities, Faculty of Philosophy, Georg August University of G¨ottingen. Table of Links Abstract and Intro
Diverse cross-document coreference and media bias analysis
Annotation tool
Annotation guidelines
Conclusion and future work
Acknowledgements
Bibliographical References 5. Conclusion and future work Our proposed annotation scheme covers a multitude of coreferential relations. It gives a detailed explanation of how to mark coreferential mentions across documents, assign entity-types and names to them, connect them with each other, and link them to the Wikidata knowledge graph. The scheme thus represents a significant step toward more accurately capturing the complexities of coreference use. It furthermore provides a valuable resource for researchers both in the field of coreference resolution and media bias by word-choice and labelling. Having said that, our scheme leaves room for possible extensions to further advance research in those domains. First, the annotation of events could be included in our scheme. An interesting question that arises is whether the relationtypes as outlined here could be applied not only to entities, but to events all the same. A second possible extension would be to include a layer of media bias annotation to the scheme, enabling a direct comparison of diverse coreference usage and media bias by word-choice and labelling. Both proposed extensions could be easily added on top of our scheme. Having said that, the present form of our scheme already addresses many of the complexities of diverse cross-document coreference and offers a roadmap for capturing nuanced linguistic relationships, ultimately advancing our understanding of language and discourse in digital print media. This paper is available on arxiv under CC 4.0 license. Authors: (1) Jakob Vogel, M.A. Digital Humanities, Institute for Digital Humanities, Faculty of Philosophy, Georg August University of G¨ottingen. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Jakob Vogel, M.A. Digital Humanities, Institute for Digital Humanities, Faculty of Philosophy, Georg August University of G¨ottingen. Table of Links Abstract and Intro Diverse cross-document coreference and media bias analysis Annotation tool Annotation guidelines Conclusion and future work Acknowledgements Bibliographical References Abstract and Intro Abstract and Intro Diverse cross-document coreference and media bias analysis Diverse cross-document coreference and media bias analysis Annotation tool Annotation tool Annotation guidelines Annotation guidelines Conclusion and future work Conclusion and future work Acknowledgements Acknowledgements Bibliographical References Bibliographical References 5. Conclusion and future work Our proposed annotation scheme covers a multitude of coreferential relations. It gives a detailed explanation of how to mark coreferential mentions across documents, assign entity-types and names to them, connect them with each other, and link them to the Wikidata knowledge graph. The scheme thus represents a significant step toward more accurately capturing the complexities of coreference use. It furthermore provides a valuable resource for researchers both in the field of coreference resolution and media bias by word-choice and labelling. Having said that, our scheme leaves room for possible extensions to further advance research in those domains. First, the annotation of events could be included in our scheme. An interesting question that arises is whether the relationtypes as outlined here could be applied not only to entities, but to events all the same. A second possible extension would be to include a layer of media bias annotation to the scheme, enabling a direct comparison of diverse coreference usage and media bias by word-choice and labelling. Both proposed extensions could be easily added on top of our scheme. Having said that, the present form of our scheme already addresses many of the complexities of diverse cross-document coreference and offers a roadmap for capturing nuanced linguistic relationships, ultimately advancing our understanding of language and discourse in digital print media.

Code Book for Annotation of Diverse Cross-Document Coreference: Annotation Guidelines

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Jakob Vogel, M.A. Digital Humanities, Institute for Digital Humanities, Faculty of Philosophy, Georg August University of G¨ottingen. Table of Links Abstract and Intro
Diverse cross-document coreference and media bias analysis
Annotation tool
Annotation guidelines
Conclusion and future work
Acknowledgements
Bibliographical References 2. Diverse cross-document coreference and media bias analysis Media bias is a multifaceted phenomenon of news coverage that is one-sided, politically shaded, or in some other way non-neutral. It can occur in all sorts of news media, though we focus on digital print media, only. One specific type of media bias is bias by word-choice and labeling (Hamborg et al., 2019). Word choice describes the selection from a variety of possible expressions to refer to an entity. For example, in order to refer to the USA’s current head of state, journalists could use one of the relatively neutral alternatives “Joe Biden”, “Biden”, or “the US president”, or in theory, choose a clearly biased expression like ”the dictator” (Kurmelovs, 2023). Labeling, on the other hand, describes the assignment of attributes to an expression, inter alia by adding adjectives. Examples for bias by labeling include “an anxious and uncertain president” or “crooked Joe Biden” (Luciano, 2023). Together, word-choice and labelling form a so-called frame (Hamborg et al., 2019). In news articles, frames are used in a variety of ways, either for the sake of linguistic diversity or to make certain, potentially biased statements about an entity. To test an article for such statements, all of an entity’s frames need to be extracted and evaluated together. Hence, before an article can be properly analyzed with regards to if and how it uses biased frames of (certain) entities, we are first faced with the task of identifying such frames. The identification of all expressions that refer to the same entity is a matter of coreference resolution. To conclude, successful coreference resolution is a prerequisite to any further inquiry of media bias by word-choice and labelling. As already indicated above, automatic coreference resolution does show good results in extracting identity clusters from a document (Liu et al., 2023). However, we have seen that there exist nearidentity relations between expressions, potentially even across documents, that would be mostly overseen by standard coreference resolution approaches (Zhukova et al., 2022). Hence, they would also be overseen by any media bias analysis that depends on coreference resolution. We hope that our building of a corpus for diverse cross-document coreference will contribute to the analysis of media bias by providing data that contains the full variety of frames used in news articles. Eventually, we would like to test how we can measure media bias by focusing on diverse coreference in news articles. To answer this last question, though, an additional layer of media bias annotation would have to be put upon our coreference data (Spinde et al., 2021a,b). This paper is available on arxiv under CC 4.0 license. Authors: (1) Jakob Vogel, M.A. Digital Humanities, Institute for Digital Humanities, Faculty of Philosophy, Georg August University of G¨ottingen. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Jakob Vogel, M.A. Digital Humanities, Institute for Digital Humanities, Faculty of Philosophy, Georg August University of G¨ottingen. Table of Links Abstract and Intro Diverse cross-document coreference and media bias analysis Annotation tool Annotation guidelines Conclusion and future work Acknowledgements Bibliographical References Abstract and Intro Abstract and Intro Diverse cross-document coreference and media bias analysis Diverse cross-document coreference and media bias analysis Annotation tool Annotation tool Annotation guidelines Annotation guidelines Conclusion and future work Conclusion and future work Acknowledgements Acknowledgements Bibliographical References Bibliographical References 2. Diverse cross-document coreference and media bias analysis Media bias is a multifaceted phenomenon of news coverage that is one-sided, politically shaded, or in some other way non-neutral. It can occur in all sorts of news media, though we focus on digital print media, only. One specific type of media bias is bias by word-choice and labeling (Hamborg et al., 2019). Word choice describes the selection from a variety of possible expressions to refer to an entity. For example, in order to refer to the USA’s current head of state, journalists could use one of the relatively neutral alternatives “Joe Biden”, “Biden”, or “the US president”, or in theory, choose a clearly biased expression like ”the dictator” (Kurmelovs, 2023). bias by word-choice and labeling Labeling, on the other hand, describes the assignment of attributes to an expression, inter alia by adding adjectives. Examples for bias by labeling include “an anxious and uncertain president” or “crooked Joe Biden” (Luciano, 2023). Together, word-choice and labelling form a so-called frame (Hamborg et al., 2019). In news articles, frames are used in a variety of ways, either for the sake of linguistic diversity or to make certain, potentially biased statements about an entity. To test an article for such statements, all of an entity’s frames need to be extracted and evaluated together. Hence, before an article can be properly analyzed with regards to if and how it uses biased frames of (certain) entities, we are first faced with the task of identifying such frames. The identification of all expressions that refer to the same entity is a matter of coreference resolution. To conclude, successful coreference resolution is a prerequisite to any further inquiry of media bias by word-choice and labelling. frame As already indicated above, automatic coreference resolution does show good results in extracting identity clusters from a document (Liu et al., 2023). However, we have seen that there exist nearidentity relations between expressions, potentially even across documents, that would be mostly overseen by standard coreference resolution approaches (Zhukova et al., 2022). Hence, they would also be overseen by any media bias analysis that depends on coreference resolution. We hope that our building of a corpus for diverse cross-document coreference will contribute to the analysis of media bias by providing data that contains the full variety of frames used in news articles. Eventually, we would like to test how we can measure media bias by focusing on diverse coreference in news articles. To answer this last question, though, an additional layer of media bias annotation would have to be put upon our coreference data (Spinde et al., 2021a,b).

Code Book for Annotation of Diverse Cross-Document Coreference: Bibliographical References

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Jakob Vogel, M.A. Digital Humanities, Institute for Digital Humanities, Faculty of Philosophy, Georg August University of G¨ottingen. Table of Links Abstract and Intro
Diverse cross-document coreference and media bias analysis
Annotation tool
Annotation guidelines
Conclusion and future work
Acknowledgements
Bibliographical References 6. Acknowledgements Many thanks to my project supervisor Anastasia Zhukova who never became tired of my many questions and always knew how to help me out with good advise whenever I felt stuck. This paper is available on arxiv under CC 4.0 license. Authors: (1) Jakob Vogel, M.A. Digital Humanities, Institute for Digital Humanities, Faculty of Philosophy, Georg August University of G¨ottingen. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Jakob Vogel, M.A. Digital Humanities, Institute for Digital Humanities, Faculty of Philosophy, Georg August University of G¨ottingen. Table of Links Abstract and Intro Diverse cross-document coreference and media bias analysis Annotation tool Annotation guidelines Conclusion and future work Acknowledgements Bibliographical References Abstract and Intro Abstract and Intro Diverse cross-document coreference and media bias analysis Diverse cross-document coreference and media bias analysis Annotation tool Annotation tool Annotation guidelines Annotation guidelines Conclusion and future work Conclusion and future work Acknowledgements Acknowledgements Bibliographical References Bibliographical References 6. Acknowledgements Many thanks to my project supervisor Anastasia Zhukova who never became tired of my many questions and always knew how to help me out with good advise whenever I felt stuck.

Code Book for Annotation of Diverse Cross-Document Coreference: Acknowledgements

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Jakob Vogel, M.A. Digital Humanities, Institute for Digital Humanities, Faculty of Philosophy, Georg August University of G¨ottingen. Table of Links Abstract and Intro
Diverse cross-document coreference and media bias analysis
Annotation tool
Annotation guidelines
Conclusion and future work
Acknowledgements
Bibliographical References 3. Annotation tool The software we will use for annotation is called Inception (Klie et al., 2018). Inception is an open source annotation tool which can be freely downloaded from the authors’ GitHub repository. Although for this project, every annotator will be provided with a ready-to-code version of the program with all necessary annotation layers and settings already implemented and some sample annotations included. This instance of Inception can be requested from the project administrator Jakob Vogel. 3.1. Setup To set up Inception on your local computer, make sure you already received your personal instance of the software. If not, please contact the project administrator. Inception comes as a jar-file. In order to run it, you need to have the Java Runtime Environment (JRE) installed. Furthermore, make sure the file is set as executable. Then open the directory ”Inception” in your command prompt and run: To access Inception’s graphical user interface (GUI), go to a web browser and open: http://localhost:8080/ On your first time running Inception, you will need to import the project and set up your personal user account: • First, log in as admin (User ID: admin ; Password: admin). • Click on ”Import project” and select the file ”proj-div-CDCR.zip” from the ”Inception” directory. Make sure to check the boxes ”Import permissions” (already checked by default) and ”Create missing users” (unchecked by default). Then click ”Import”. • Click on ”Administration” in the GUI’s right top corner. Then click on ”Users”. • Select your personal user or create a new one here. Assign a password to your user. Additionally, assign the role ”ROLE USER” to your user (already assigned by default). Finally, check the box ”Account enabled” and click ”Save”. • Log out of the current Inception session. From now on, to log into Inception, use your personal user account details instead of the admin account. To get to the annotation GUI, log in with your personal account now and click on the highlighted project name ”Diverse cross-document coreference”. Then, in the left taskbar, click on ”Annotation”. A window opens that shows a list of all documents to be annotated. The first digit in every title is a discourse identifier that sorts all documents according to their topic, followed by an underscore and a newspaper abbreviation (see Introduction). You can annotate documents in chronological order or randomly, whichever you prefer. Click on one of the documents to start your annotation. 3.2. User manual Inception offers a variety of functionalities of which only those relevant for our project are described here. For a full explanation of how to use Inception, please check the official documentation which can be accessed online or from within the Inception GUI by clicking on ”Help” in the right upper corner. Every annotator’s instance of Inception contains two basic layers of annotation. The first layer, called Entity layer, is triggered when a mention is marked by highlighting text with a simple press-hold-drag mechanism. This opens the layer’s side panel. Here, annotators can fill in the Entity layer’s three parameters: • Entity-type: a drop-down list to select a mention’s entity-type by clicking on or typing the type’s abbreviation. • Global entity-name: a mixture of free textfield and drop-down list to assign a global entity’s name to a mention. If the name has already been used before, it can be selected as item from the drop-down list by again clicking or typing. If not, it can be freely typed which adds it as a new tag to the list. • Wikidata: a search field to type the name of an entity and find its respective Wikidata URI. item from the drop-down list by again clicking or typing. If not, it can be freely typed which adds it as a new tag to the list. • Wikidata: a search field to type the name of an entity and find its respective Wikidata URI. The second layer, called Relation, is triggered when two already marked mentions are connected to each other, again simply by clicking and holding on one mention and dragging the mouse to the other mention. This layer only contains one parameter which is named Label. It is a drop-down list to select a relation-type for labelling the connection between both mentions. After the first annotations have been made, Inception starts to suggests spans and values for new annotations on the Entity layer. These suggestions are displayed in gray boxes. One click on a box accepts the suggestion and turns it into a proper annotation, a double-click denies the suggestion and makes the box disappear. The GUI’s upper panel is mostly for navigating through the document. However, it also contains a button for resetting the document by deleting all annotations made so far and a button in the shape of a padlock to mark the annotation process of the document as finished. This button should be pressed at the very end of the annotation, though it is advisable to first annotate each document before marking all of them together as officially finished. Clicking on the gear wheel opens up the GUI’s style settings. Here, annotators have the option to adjust panels’ margin sizes, the colouring of annotations, and how many text rows are to be displayed simultaneously. Annotations are saved automatically which is why there exists no saving button in the GUI. This paper is available on arxiv under CC 4.0 license. Authors: (1) Jakob Vogel, M.A. Digital Humanities, Institute for Digital Humanities, Faculty of Philosophy, Georg August University of G¨ottingen. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Jakob Vogel, M.A. Digital Humanities, Institute for Digital Humanities, Faculty of Philosophy, Georg August University of G¨ottingen. Table of Links Abstract and Intro Diverse cross-document coreference and media bias analysis Annotation tool Annotation guidelines Conclusion and future work Acknowledgements Bibliographical References Abstract and Intro Abstract and Intro Diverse cross-document coreference and media bias analysis Diverse cross-document coreference and media bias analysis Annotation tool Annotation tool Annotation guidelines Annotation guidelines Conclusion and future work Conclusion and future work Acknowledgements Acknowledgements Bibliographical References Bibliographical References 3. Annotation tool The software we will use for annotation is called Inception (Klie et al., 2018). Inception is an open source annotation tool which can be freely downloaded from the authors’ GitHub repository. Although for this project, every annotator will be provided with a ready-to-code version of the program with all necessary annotation layers and settings already implemented and some sample annotations included. This instance of Inception can be requested from the project administrator Jakob Vogel. Inception 3.1. Setup To set up Inception on your local computer, make sure you already received your personal instance of the software. If not, please contact the project administrator. Inception comes as a jar-file. In order to run it, you need to have the Java Runtime Environment (JRE) installed. Furthermore, make sure the file is set as executable. Then open the directory ”Inception” in your command prompt and run: To access Inception’s graphical user interface (GUI), go to a web browser and open: http://localhost:8080/ On your first time running Inception, you will need to import the project and set up your personal user account: • First, log in as admin (User ID: admin ; Password: admin). • Click on ”Import project” and select the file ”proj-div-CDCR.zip” from the ”Inception” directory. Make sure to check the boxes ”Import permissions” (already checked by default) and ”Create missing users” (unchecked by default). Then click ”Import”. • Click on ”Administration” in the GUI’s right top corner. Then click on ”Users”. • Select your personal user or create a new one here. Assign a password to your user. Additionally, assign the role ”ROLE USER” to your user (already assigned by default). Finally, check the box ”Account enabled” and click ”Save”. • Log out of the current Inception session. From now on, to log into Inception, use your personal user account details instead of the admin account. To get to the annotation GUI, log in with your personal account now and click on the highlighted project name ”Diverse cross-document coreference”. Then, in the left taskbar, click on ”Annotation”. A window opens that shows a list of all documents to be annotated. The first digit in every title is a discourse identifier that sorts all documents according to their topic, followed by an underscore and a newspaper abbreviation (see Introduction). You can annotate documents in chronological order or randomly, whichever you prefer. Click on one of the documents to start your annotation. 3.2. User manual Inception offers a variety of functionalities of which only those relevant for our project are described here. For a full explanation of how to use Inception, please check the official documentation which can be accessed online or from within the Inception GUI by clicking on ”Help” in the right upper corner. Every annotator’s instance of Inception contains two basic layers of annotation. The first layer, called Entity layer , is triggered when a mention is marked by highlighting text with a simple press-hold-drag mechanism. This opens the layer’s side panel. Here, annotators can fill in the Entity layer’s three parameters: Entity layer • Entity-type: a drop-down list to select a mention’s entity-type by clicking on or typing the type’s abbreviation. • Entity-type: • Global entity-name: a mixture of free textfield and drop-down list to assign a global entity’s name to a mention. If the name has already been used before, it can be selected as item from the drop-down list by again clicking or typing. If not, it can be freely typed which adds it as a new tag to the list. • Global entity-name: • Wikidata : a search field to type the name of an entity and find its respective Wikidata URI. Wikidata item from the drop-down list by again clicking or typing. If not, it can be freely typed which adds it as a new tag to the list. • Wikidata: a search field to type the name of an entity and find its respective Wikidata URI. The second layer, called Relation , is triggered when two already marked mentions are connected to each other, again simply by clicking and holding on one mention and dragging the mouse to the other mention. This layer only contains one parameter which is named Label . It is a drop-down list to select a relation-type for labelling the connection between both mentions. Relation Label After the first annotations have been made, Inception starts to suggests spans and values for new annotations on the Entity layer. These suggestions are displayed in gray boxes. One click on a box accepts the suggestion and turns it into a proper annotation, a double-click denies the suggestion and makes the box disappear. The GUI’s upper panel is mostly for navigating through the document. However, it also contains a button for resetting the document by deleting all annotations made so far and a button in the shape of a padlock to mark the annotation process of the document as finished. This button should be pressed at the very end of the annotation, though it is advisable to first annotate each document before marking all of them together as officially finished. Clicking on the gear wheel opens up the GUI’s style settings. Here, annotators have the option to adjust panels’ margin sizes, the colouring of annotations, and how many text rows are to be displayed simultaneously. Annotations are saved automatically which is why there exists no saving button in the GUI.

Diverse Cross-document Coreference and Media Bias Analysis 

Code Book for Annotation of Diverse Cross-Document Coreference: Annotation Tool

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Jakob Vogel, M.A. Digital Humanities, Institute for Digital Humanities, Faculty of Philosophy, Georg August University of G¨ottingen. Table of Links Abstract and Intro
Diverse cross-document coreference and media bias analysis
Annotation tool
Annotation guidelines
Conclusion and future work
Acknowledgements
Bibliographical References Abstract This paper presents a scheme for annotating coreference across news articles, extending beyond traditional identity relations by also considering near-identity and bridging relations. It includes a precise description of how to set up Inception, a respective annotation tool, how to annotate entities in news articles, connect them with diverse coreferential relations, and link them across documents to Wikidata’s global knowledge graph. This multi-layered annotation approach is discussed in the context of the problem of media bias. Our main contribution lies in providing a methodology for creating a diverse cross-document coreference corpus which can be applied to the analysis of media bias by word-choice and labelling. Keywords: coreference resolution, diverse coreference annotation, entity annotation, entity linking, media bias analysis, natural language processing 1. Introduction Coreference is the phenomenon of several expressions in a text all referring to the same person, object, or other entity or event as their referent. Thus, in a narrow sense, analyzing a document with regards to coreference means detecting relations of identity between phrases. The following example (1) illustrates such an identity relation, where coreferential expressions are printed in italics: (1) “Joe Biden arrived in Berlin yesterday, but the president did not come alone.” In (1), the noun phrase “Joe Biden” introduces a new entity while “the president” relates back to that introducing phrase. Within this relation, the introducing phrase “Joe Biden” is called the antecedent while the back-relating phrase “the president” is called an anaphor. Both expressions are coreferential in the way that they refer to the same non-textual entity, namely to the actual ‘realworld’ Joe Biden or at least to a corresponding mental concept. We can think of an antecedent and its anaphora as forming a cluster of mentions that as a whole represents its extra-textual referent within a textual document, as shown in Figure 1. As a task of natural language processing (NLP), coreference resolution has become quite efficient in detecting identity relations between phrases. However, reflecting on how we use language to refer to something, we are forced to realize that coreference in a broader sense is actually far more complex. We can address an entity or event by using a variety of expressions that are in fact not strictly identical to each other. Consider the following examples: (2) “President Biden was clearly not satisfied with today’s outcome. As the White House stated this afternoon, efforts will be made to . . . ” (3) “Even if the young Erdogan used to be pro-Western, Turkey’s president nowadays often acts against Western interests.” (4) “The AfD is circulating a photo of Angela Merkel with a Hijab, although Merkel never wore Muslim clothes.” In these given examples, the highlighted mentions mean ‘almost’ the same, but not completely. In (2), we are aware by world-knowledge that ”the White House” is often used as a substitute expression for the current US president, although the former is a place which in strict terms cannot be identical to the president, who is a person. In (3), on the other hand, both mentions refer to the ’real-world’ person Erdogan, but at different time steps. Finally, in (4), a mention representing the person Merkel is juxtaposed with a mention representing a picture of Merkel. While these two mentions could refer to separate entities, the juxtaposition indicates a connection between both where the attributes of the first mention do influence the perception of the second mention. Hence, we would miss essential semantic connections if we chose not to mark them as coreferential. Having said that, the simple classification of two mentions into coreferential (identical) or noncoreferential (non-identical) does not seem to suffice the complexity of common text data. Instead, we need to allow for diverse coreference clusters that include finer-grained relations lying between identity and non-identity. We need to allow for near-identity relations to mark two mentions that are partially, but not totally, identical (Recasens et al., 2010). In news coverage, identity and near-identity references are extensively used to report on persons, organizations, and other entities of public interest. It is our goal to build up a corpus that contains annotated examples of such diverse forms of coreference. While diverse coreference occurs in all sorts of news media, we focus on digital print media, only. Furthermore, although in practice both entities and events can act as referent, we ignore references to events for now, as their annotation would go beyond the limits of our present scheme.[1] The ordinary business of journalism is to write about current political affairs and other happenings of public interest. These happenings are normally reported by several newspapers at the same time. All of these news articles are considered documents that contain references to the same entities and together form a discourse about them. To include the whole picture of such intradiscursive references, we want our corpus to link document-level clusters with corresponding clusters of other documents of the same discourse. Hence, our corpus is to depict cross-document coreference data. On a discourse level, corresponding clusters form discourse entities that themselves can be linked to their non-textual referents by some knowledge graph identifier. For this project, we use Wikidata’s Uniform Resource Identifiers (URIs) for entity linking. By doing so, world knowledge is included into the data. This allows for drawing connections even between different discourse entities that refer to a common referent, yet at a different time step or rather in the context of a different happening. Figure 2 illustrates the multiple layers of this annotation model. In building a corpus for diverse cross-document coreference in news articles, we hope to provide a valuable resource for the evaluation of automated coreference resolution tasks. The contribution of this paper mainly lies in providing an answer to the question of how to create such a corpus. How can diverse coreference relations be annotated in a cross-document setup? We believe our scheme as we present it here tackles this problem efficiently, extensively, and unambiguously. Additionally, we would like to use the data resulting from our own annotations for further research in the area of media bias. Even if it plays no direct part in the outlined scheme, a lot of our choices how to annotate references were made because of this requirement to make the data usable for later media bias analysis. Eventually, we hope to contribute to the wider research question of how to identify media bias by word choice and labelling based on the usage of diverse coreference relations in news articles. The following section 2 will further elaborate on this connection between diverse coreference and the problem of media bias analysis. Despite its only subtle impact on our practical annotation instructions, that section means to highlight the theoretical background and motivation behind our project. The sections thereafter will then deal with the actual annotation process. Section 3 will guide coders through the setup and controls of Inception, our selected annotation software. Finally, section 4 will define annotation instructions in three passes while also outlining our typology of diverse coreference. The data we use for our own annotations consists of the text bodies of articles that report on the same happenings. All articles are in English and were published by one of the following US-American newspapers: HuffPost (categorized as ”Left” by AllSides (2023) or ”Skews Left” by Ad Fontes Media (2023), abbreviated in our data as ”LL”), The New York Times (categorized as ”Lean Left” by AllSides or ”Skews Left” by Ad Fontes Media, abbreviated as ”L”), USA Today (categorized as ”Lean Left” or ”Middle or Balanced Bias”, abbreviated as ”M”), Fox News (categorized as ”Right” or ”Skews Right”, abbreviated as ”R”), Breitbart News Network (categoized as ”Right” or ”Strong Right”, abbreviated as ”RR”).[2] [1] Though at a later point, this scheme could be extended to also include the annotation of events (Linguistic Data Consortium, 2005; O’Gorman et al., 2016). [2] Looking at the political orientation of these newspapers, the data is unbalanced with an underrepresentation of politically centered media. However, at the current state of this project, the imbalance is unlikely to influence our analysis which does not yet target political orientation or media bias itself. Therefore, we will ignore this issue for now. This paper is available on arxiv under CC 4.0 license. Authors: (1) Jakob Vogel, M.A. Digital Humanities, Institute for Digital Humanities, Faculty of Philosophy, Georg August University of G¨ottingen. This paper is available on arxiv under CC 4.0 license. Authors: Authors: (1) Jakob Vogel, M.A. Digital Humanities, Institute for Digital Humanities, Faculty of Philosophy, Georg August University of G¨ottingen. Table of Links Abstract and Intro Diverse cross-document coreference and media bias analysis Annotation tool Annotation guidelines Conclusion and future work Acknowledgements Bibliographical References Abstract and Intro Abstract and Intro Diverse cross-document coreference and media bias analysis Diverse cross-document coreference and media bias analysis Annotation tool Annotation tool Annotation guidelines Annotation guidelines Conclusion and future work Conclusion and future work Acknowledgements Acknowledgements Bibliographical References Bibliographical References Abstract This paper presents a scheme for annotating coreference across news articles, extending beyond traditional identity relations by also considering near-identity and bridging relations. It includes a precise description of how to set up Inception, a respective annotation tool, how to annotate entities in news articles, connect them with diverse coreferential relations, and link them across documents to Wikidata’s global knowledge graph. This multi-layered annotation approach is discussed in the context of the problem of media bias. Our main contribution lies in providing a methodology for creating a diverse cross-document coreference corpus which can be applied to the analysis of media bias by word-choice and labelling. Keywords : coreference resolution, diverse coreference annotation, entity annotation, entity linking, media bias analysis, natural language processing Keywords 1. Introduction Coreference is the phenomenon of several expressions in a text all referring to the same person, object, or other entity or event as their referent. Thus, in a narrow sense, analyzing a document with regards to coreference means detecting relations of identity between phrases. The following example (1) illustrates such an identity relation, where coreferential expressions are printed in italics: (1) “Joe Biden arrived in Berlin yesterday, but the president did not come alone.” In (1), the noun phrase “Joe Biden” introduces a new entity while “the president” relates back to that introducing phrase. Within this relation, the introducing phrase “Joe Biden” is called the antecedent while the back-relating phrase “the president” is called an anaphor. Both expressions are coreferential in the way that they refer to the same non-textual entity, namely to the actual ‘realworld’ Joe Biden or at least to a corresponding mental concept. We can think of an antecedent and its anaphora as forming a cluster of mentions that as a whole represents its extra-textual referent within a textual document, as shown in Figure 1. As a task of natural language processing (NLP), coreference resolution has become quite efficient in detecting identity relations between phrases. However, reflecting on how we use language to refer to something, we are forced to realize that coreference in a broader sense is actually far more complex. We can address an entity or event by using a variety of expressions that are in fact not strictly identical to each other. Consider the following examples: (2) “ President Biden was clearly not satisfied with today’s outcome. As the White House stated this afternoon, efforts will be made to . . . ” President Biden the White House (3) “Even if the young Erdogan used to be pro-Western, Turkey’s president nowadays often acts against Western interests.” the young Erdogan Turkey’s president (4) “The AfD is circulating a photo of Angela Merkel with a Hijab , although Merkel never wore Muslim clothes.” a photo of Angela Merkel with a Hijab In these given examples, the highlighted mentions mean ‘almost’ the same, but not completely. In (2), we are aware by world-knowledge that ” the White House ” is often used as a substitute expression for the current US president, although the former is a place which in strict terms cannot be identical to the president, who is a person. In (3), on the other hand, both mentions refer to the ’real-world’ person Erdogan, but at different time steps. Finally, in (4), a mention representing the person Merkel is juxtaposed with a mention representing a picture of Merkel. While these two mentions could refer to separate entities, the juxtaposition indicates a connection between both where the attributes of the first mention do influence the perception of the second mention. Hence, we would miss essential semantic connections if we chose not to mark them as coreferential. Having said that, the simple classification of two mentions into coreferential (identical) or noncoreferential (non-identical) does not seem to suffice the complexity of common text data. Instead, we need to allow for diverse coreference clusters that include finer-grained relations lying between identity and non-identity. We need to allow for near-identity relations to mark two mentions that are partially, but not totally, identical (Recasens et al., 2010). the White House diverse coreference near-identity In news coverage, identity and near-identity references are extensively used to report on persons, organizations, and other entities of public interest. It is our goal to build up a corpus that contains annotated examples of such diverse forms of coreference. While diverse coreference occurs in all sorts of news media, we focus on digital print media, only. Furthermore, although in practice both entities and events can act as referent, we ignore references to events for now, as their annotation would go beyond the limits of our present scheme.[1] The ordinary business of journalism is to write about current political affairs and other happenings of public interest. These happenings are normally reported by several newspapers at the same time. All of these news articles are considered documents that contain references to the same entities and together form a discourse about them. To include the whole picture of such intradiscursive references, we want our corpus to link document-level clusters with corresponding clusters of other documents of the same discourse. Hence, our corpus is to depict cross-document coreference data. On a discourse level, corresponding clusters form discourse entities that themselves can be linked to their non-textual referents by some knowledge graph identifier. For this project, we use Wikidata’s Uniform Resource Identifiers (URIs) for entity linking. By doing so, world knowledge is included into the data. This allows for drawing connections even between different discourse entities that refer to a common referent, yet at a different time step or rather in the context of a different happening. Figure 2 illustrates the multiple layers of this annotation model. In building a corpus for diverse cross-document coreference in news articles, we hope to provide a valuable resource for the evaluation of automated coreference resolution tasks. The contribution of this paper mainly lies in providing an answer to the question of how to create such a corpus. How can diverse coreference relations be annotated in a cross-document setup? We believe our scheme as we present it here tackles this problem efficiently, extensively, and unambiguously. Additionally, we would like to use the data resulting from our own annotations for further research in the area of media bias. Even if it plays no direct part in the outlined scheme, a lot of our choices how to annotate references were made because of this requirement to make the data usable for later media bias analysis. Eventually, we hope to contribute to the wider research question of how to identify media bias by word choice and labelling based on the usage of diverse coreference relations in news articles. The following section 2 will further elaborate on this connection between diverse coreference and the problem of media bias analysis. Despite its only subtle impact on our practical annotation instructions, that section means to highlight the theoretical background and motivation behind our project. The sections thereafter will then deal with the actual annotation process. Section 3 will guide coders through the setup and controls of Inception, our selected annotation software. Finally, section 4 will define annotation instructions in three passes while also outlining our typology of diverse coreference. The data we use for our own annotations consists of the text bodies of articles that report on the same happenings. All articles are in English and were published by one of the following US-American newspapers: HuffPost (categorized as ”Left” by AllSides (2023) or ”Skews Left” by Ad Fontes Media (2023), abbreviated in our data as ”LL”), The New York Times (categorized as ”Lean Left” by AllSides or ”Skews Left” by Ad Fontes Media, abbreviated as ”L”), USA Today (categorized as ”Lean Left” or ”Middle or Balanced Bias”, abbreviated as ”M”), Fox News (categorized as ”Right” or ”Skews Right”, abbreviated as ”R”), Breitbart News Network (categoized as ”Right” or ”Strong Right”, abbreviated as ”RR”).[2] [1] Though at a later point, this scheme could be extended to also include the annotation of events (Linguistic Data Consortium, 2005; O’Gorman et al., 2016). [2] Looking at the political orientation of these newspapers, the data is unbalanced with an underrepresentation of politically centered media. However, at the current state of this project, the imbalance is unlikely to influence our analysis which does not yet target political orientation or media bias itself. Therefore, we will ignore this issue for now.

Code Book for Annotation of Diverse Cross-Document Coreference: Abstract and Intro

\MARSEILLE, France, May 15th, 2024/Chainwire/--CROSS THE AGES(CTA),a multimedia gaming ecosystem, announced a $3.5 million equity round of funding, led by Animoca Brands. With additional investments from Sebastien Borget of The Sandbox and Nicolas Jeuffrain of Tenergie, this funding round builds upon $15 million raised from investors, totaling $23.5M in funding to date including community fundraising. The funds raised are being announced alongside the ecosystem’s Token Generation Event (TGE), with exchanges such as Bybit, KuCoin, GATE and MEXC listing the token. With this strategic investment, CROSS THE AGES is set to accelerate its many growth initiatives and build out the CTA universe and ecosystem. Since the release of its virtual trading card game in March 2023, CROSS THE AGES has garnered over 400k downloads and 148k monthly active users. “We are thrilled to welcome Animoca Brands as the lead investor in our first equity round,” said Sami Chlagou, CEO and Co-founder of CROSS THE AGES. “This collaboration signifies a shared commitment and a vote of confidence for CTA’s gaming universe to expand the IP amongst Animoca brands ecosystems and partners .”“Blockchain gaming is an important movement that is bringing true digital ownership to the masses” commented Yat Siu, the executive chairman and co-founder of Animoca Brands. “Cross The Ages perfectly embodies the values of this movement, enabling users to live experiences in a virtual environment solidly founded upon personal ownership.” About CROSS THE AGES Launched in 2020, CROSS THE AGES (CTA) is a transmedia intellectual property (IP) where futuristic fantasy meets sci-fi epic narrative. Leveraging blockchain technology, the CTA universe sets a new benchmark in innovative gaming, combining free-to-play and play-to-earn. The experiential ecosystem blends the virtual and real worlds, encompassing books, comics, gaming, esports, animation, collectibles, and an underlying gaming investment model to promote the transition to renewable energy in the real world. Already boasting partnerships with industry leaders like Ubisoft and Square Enix, CROSS THE AGES continues to push the boundaries of innovation in gaming and entertainment. For more information visit crosstheages.com/en-us. Website | X | YouTube | Instagram | Discord | Twitch Contact Chief Marketing Officer Patrick Mercanton patrick.m@crosstheages.com This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. \MARSEILLE, France, May 15th, 2024/Chainwire/--CROSS THE AGES(CTA),a multimedia gaming ecosystem, announced a $3.5 million equity round of funding, led by Animoca Brands . With additional investments from Sebastien Borget of The Sandbox and Nicolas Jeuffrain of Tenergie, this funding round builds upon $15 million raised from investors, totaling $23.5M in funding to date including community fundraising. Animoca Brands Animoca Brands The funds raised are being announced alongside the ecosystem’s Token Generation Event (TGE), with exchanges such as Bybit, KuCoin, GATE and MEXC listing the token. With this strategic investment, CROSS THE AGES is set to accelerate its many growth initiatives and build out the CTA universe and ecosystem. Since the release of its virtual trading card game in March 2023, CROSS THE AGES has garnered over 400k downloads and 148k monthly active users. “We are thrilled to welcome Animoca Brands as the lead investor in our first equity round,” said Sami Chlagou, CEO and Co-founder of CROSS THE AGES. “This collaboration signifies a shared commitment and a vote of confidence for CTA’s gaming universe to expand the IP amongst Animoca brands ecosystems and partners .”“Blockchain gaming is an important movement that is bringing true digital ownership to the masses” commented Yat Siu, the executive chairman and co-founder of Animoca Brands. “Cross The Ages perfectly embodies the values of this movement, enabling users to live experiences in a virtual environment solidly founded upon personal ownership.” About CROSS THE AGES Launched in 2020, CROSS THE AGES (CTA) is a transmedia intellectual property (IP) where futuristic fantasy meets sci-fi epic narrative. Leveraging blockchain technology, the CTA universe sets a new benchmark in innovative gaming, combining free-to-play and play-to-earn. The experiential ecosystem blends the virtual and real worlds, encompassing books, comics, gaming, esports, animation, collectibles, and an underlying gaming investment model to promote the transition to renewable energy in the real world. Already boasting partnerships with industry leaders like Ubisoft and Square Enix, CROSS THE AGES continues to push the boundaries of innovation in gaming and entertainment. For more information visit crosstheages.com/en-us . Website | X | YouTube | Instagram | Discord | Twitch crosstheages.com/en-us crosstheages.com/en-us Website Website X X YouTube YouTube Instagram Instagram Discord Discord Twitch Twitch Contact Chief Marketing Officer Patrick Mercanton patrick.m@crosstheages.com This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here . here here

CROSS THE AGES Raises $3.5M In Equity Round Led By Animoca Brands And Lists On Major Exchanges

**SINGAPORE, Singapore, May 15th, 2024/Chainwire/--**ETFSwap(ETFS),an emerging decentralized cryptocurrency and Exchange-Traded Funds (ETFS) platform, has achieved a series of significant milestones, marking a historic moment in its development and presale. With the support and confidence of thousands of users and investors worldwide, this ground-breaking platform is experiencing a meteoric rise in popularity. In addition, ETFSwap (ETFS) is gaining global recognition as a significant player in the tokenized ETF market. It offers a platform that is both distinctive and accessible, as well as unique and user-friendly, for trading cryptocurrencies and ETFs. ETFSwap (ETFS) Records Unprecedented Surge To Cross 4,000 Users As of November 2023, the global ETFs industry reached a valuation of $10.99 trillion and has been growing rapidly ever since. Given this expansion, an increasing number of cryptocurrency enthusiasts and investors have looked for ways to engage with the potential in this sector. ETFSwap (ETFS) emerges as a bridge between the traditional and Decentralized Finance (DeFi) ecosystem. This platform offers investment opportunities for global investors, exposing them to trillion-dollar sectors such as health, energy, technology, commodities, and more. ETFSwap (ETFS) offers crypto investors a novel service that has never been seen in the industry. It allows access to the trillion-dollar traditional ETFs market, allowing them to expand their investment portfolio by tokenizing these assets for easy trading. But perhaps where ETFSwap (ETFS) really outpaces its competitors is that it presents an easy on-and-off ramp for trading ETFs using both crypto and fiat, coupled with the decentralization of the Ethereum blockchain. Over the next year, the platform plans to complete its roadmap with the full launch of the ETFSwap (ETFS) trading platform open for all. Additionally, it’ll launch its partnership program, launch its staking decentralized application (DApp), and roll out community rewards. Its token will launch on decentralized exchanges such as Uniswap, with open public trading to follow. This comes with a full-blown marketing roll-out such as CoinMarketCap fast-track, Key Opinion Leaders (KOLs), and token competitions. The ETFSwap (ETFS) platform has undergone a rigorous audit by CyberScope, a leader in the blockchain security industry. The audit found no vulnerabilities in its contract, with the company declaring it safe for investment. Ahead of its full platform launch, the company is focused on securing all necessary licenses required to bring this novel service to investors worldwide. To sweeten the pot, it requires no KYC (Know Your Customer), which means investors just need to connect their wallet to start trading on the website. ETFSwap (ETFS) is already seeing unparalleled adoption amongst users across diverse regions globally. Currently, the innovative platform has recorded more than 4,000 users in just a few weeks. This surge in adoption is fueled not only by ETFSwap’s (ETFS) advanced trading technology and capabilities but also by the rising interest in tokenized ETFs within the digital asset landscape. Key Milestones and Presale Progress Thanks to ETFSwap users’, ETFSwap (ETFS) has successfully hit key developmental milestones. With the help of institutional investors, ETFSwap (ETFS) successfully raised over $750,000 in its private fundraising round. In addition to the growth of ETFSwap's user base, the first stage of the ongoing presale has seen over 75 million tokens sold. The ETFSwap team noticed the increase in sales and, with a strategic decision, has raised the ETFS token price from $0.00854 in its first presale stage to $0.01831 during the second stage. The public presale has also collectively raised over $1.5 million in a few weeks. For more information about the ETFS Presale: Users can visit ETFSwap Presale Users can join The ETFSwap Community Contact Jacob Moss ETFSwap LLC info@etfswap.io This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. **SINGAPORE, Singapore, May 15th, 2024/Chainwire/--**ETFSwap(ETFS),an emerging decentralized cryptocurrency and Exchange-Traded Funds (ETFS) platform, has achieved a series of significant milestones, marking a historic moment in its development and presale. With the support and confidence of thousands of users and investors worldwide, this ground-breaking platform is experiencing a meteoric rise in popularity. In addition, ETFSwap (ETFS) is gaining global recognition as a significant player in the tokenized ETF market. It offers a platform that is both distinctive and accessible, as well as unique and user-friendly, for trading cryptocurrencies and ETFs. ETFSwap (ETFS) Records Unprecedented Surge To Cross 4,000 Users As of November 2023, the global ETFs industry reached a valuation of $10.99 trillion and has been growing rapidly ever since. Given this expansion, an increasing number of cryptocurrency enthusiasts and investors have looked for ways to engage with the potential in this sector. ETFSwap (ETFS) emerges as a bridge between the traditional and Decentralized Finance (DeFi) ecosystem. This platform offers investment opportunities for global investors, exposing them to trillion-dollar sectors such as health, energy, technology, commodities, and more. ETFSwap (ETFS) offers crypto investors a novel service that has never been seen in the industry. It allows access to the trillion-dollar traditional ETFs market, allowing them to expand their investment portfolio by tokenizing these assets for easy trading. But perhaps where ETFSwap (ETFS) really outpaces its competitors is that it presents an easy on-and-off ramp for trading ETFs using both crypto and fiat, coupled with the decentralization of the Ethereum blockchain. ETFSwap (ETFS) ETFSwap (ETFS) Over the next year, the platform plans to complete its roadmap with the full launch of the ETFSwap (ETFS) trading platform open for all. Additionally, it’ll launch its partnership program, launch its staking decentralized application (DApp), and roll out community rewards. Its token will launch on decentralized exchanges such as Uniswap, with open public trading to follow. This comes with a full-blown marketing roll-out such as CoinMarketCap fast-track, Key Opinion Leaders (KOLs), and token competitions. The ETFSwap (ETFS) platform has undergone a rigorous audit by CyberScope , a leader in the blockchain security industry. The audit found no vulnerabilities in its contract, with the company declaring it safe for investment. Ahead of its full platform launch, the company is focused on securing all necessary licenses required to bring this novel service to investors worldwide. To sweeten the pot, it requires no KYC (Know Your Customer), which means investors just need to connect their wallet to start trading on the website. CyberScope CyberScope ETFSwap (ETFS) is already seeing unparalleled adoption amongst users across diverse regions globally. Currently, the innovative platform has recorded more than 4,000 users in just a few weeks. This surge in adoption is fueled not only by ETFSwap’s (ETFS) advanced trading technology and capabilities but also by the rising interest in tokenized ETFs within the digital asset landscape. Key Milestones and Presale Progress Thanks to ETFSwap users’, ETFSwap (ETFS) has successfully hit key developmental milestones. With the help of institutional investors, ETFSwap (ETFS) successfully raised over $750,000 in its private fundraising round. In addition to the growth of ETFSwap's user base, the first stage of the ongoing presale has seen over 75 million tokens sold. The ETFSwap team noticed the increase in sales and, with a strategic decision, has raised the ETFS token price from $0.00854 in its first presale stage to $0.01831 during the second stage. The public presale has also collectively raised over $1.5 million in a few weeks. raised over $1.5 million raised over $1.5 million For more information about the ETFS Presale: Users can visit ETFSwap Presale Users can visit ETFSwap Presale Users can visit ETFSwap Presale Users can join The ETFSwap Community Users can join The ETFSwap Community Users can join The ETFSwap Community Contact Jacob Moss ETFSwap LLC info@etfswap.io This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here. This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here . here here

ETFSwap (ETFS) Crosses 4,000 Users With $1.5 Million Raised

Imagining a world less economically interconnected than our current one is challenging. Yet, three decades ago, global interactions were markedly different – companies engaged in significantly fewer cross-border payments and were predominantly focused on domestic endeavors. Fast forward to today’s borderless global economy reliant on international supply chains, remote workforces, and API-first tech stacks, and the siloed business models of yesteryear have nearly completed their relegation to obsolescence. With a persistent desire to increase the speed of processes across organizations and government agendas worldwide, there is a modern imperative to streamline cross-border payments to improve efficacy. However, fraud is the primary challenge contributing friction to the objective at hand. Two Aspects to Improve: Speed & Security The surge in cross-border payments, driven by trade, capital, and migration flows, is only expected to climb – with a reported __ __With such expected growth comes a need to improve the efficiency and speed of cross-border payments, as evidenced by conversations led by the European Union in recent times. $190 trillion in 2023 projected to reach $290 trillion by 2030. In October 2022, the European Commission introduced a legislative proposal aimed at enabling citizens with bank accounts in the European Economic Area to execute instant euro payments. Earlier this month, the legislation was officially passed, with banks and payment service providers now mandated to allow EU citizens and businesses to conduct nearly instantaneous credit transfers. Despite significant growth, cross-border payments remain expensive and sluggish with fees , and a timeframe that can take up to several days for payments to complete. Reducing the cost, speeding up the process, and enhancing the accessibility of cross-border payments would yield significant advantages, particularly in emerging and developing economies. averaging 1.5% for corporations, 6.3% for remittances The critical challenge for companies engaged in this field is to devise strategies that effectively balance the two aspects of speed and security; to serve customers' ideal desires of near-instantaneous payments that are completely secure. The Cross-Border Payments Fraud Problem Unfortunately, this is easier said than done. While only representing 11% of total card payment transactions, cross-border payments accounted for . Fraudsters are particularly drawn to cross-border payments because they can easily steal funds, often as a result of weak security measures. 63% of card fraud Most notably, the physical distance between the fraudsters and their victims significantly lowers the chances of the perpetrators being caught. Since victims have limited options for recourse after being defrauded, cross-border payments are frequently seen as the easiest opportunity for fraudsters to execute scams. How Fraud Undermines Trust Increasing fraud rates have the potential to erode trust in the security of cross-border payments, and a loss of faith in the security of these payments could lead to an eventual decline, diminishing the future viability of businesses dependent on an international marketplace. Victims of cross-border payment fraud are ensnared by an array of sophisticated tactics. In Account Takeover (ATO) fraud, perpetrators gain unauthorized access to victims' banking or digital wallet accounts, manipulating them for illicit transactions. Even within the broader fraud threat landscape, account takeovers are a growing problem, with an estimated 22% of adults in the US falling victim to this type of fraud in 2022. Another popular method is chargeback fraud, which involves deceitful transaction reversals, while stolen card fraud sees the unauthorized use of credit or debit card details for fraudulent purchases or withdrawals. While sometimes referred to as ‘friendly fraud,’ chargeback fraud can be far from pleasant and is growing at a rate of around 41% a year. Cross-border payments are also susceptible to fraudsters looking to commit money laundering. Money laundering intricately disguises the origins of illicit funds, complicating efforts to trace them back to criminal activities. Once again, this is a huge fraud problem generally. In fact, anti-money laundering fines were up 50% last year alone. Other forms of fraud affecting the cross-border payment process include BIN attacks, triangulation fraud, and Authorized Push Payment (APP). Together, these tactics not only inflict financial losses but can also severely damage victims’ credit history and erode trust in digital financial transactions across the board. New Ways to Address Old Problems The answer to addressing fraud in cross-border payments is to get proactive and stop the issue before it occurs. Unfortunately, traditional risk technologies have been expensive to develop, slow to implement, complex, and ultimately, unable to keep pace with evolving fraud trends. Thankfully, new solutions are now coming to the fore that offer significant improvements. Artificial intelligence (AI) advancements have opened new avenues to address these challenges. Through advanced digital footprinting and the power of machine learning, modern fraud prevention solutions that leverage AI can find the tell-tale signs of fraud that humans tend to miss and help to stop it in its tracks. For companies like SEON, the ability to enrich data is key to this effort. Without always realizing it, users regularly leave behind digital footprints on the sites they visit. By analyzing this information, solutions like ours can unlock the likelihood of an individual being fraudulent while simultaneously making other critical determinations around online accounts. Fraud prevention solutions that leverage AI have the potential to impart considerable new trust across the cross-border payment space. Whether it’s leveraging behavioral analysis techniques to spot anomalies in user behaviors that indicate account takeovers or utilizing transaction monitoring to spot any unusual transfers of funds, the technology could be transformative. Maintaining Trust In the context of cross-border money transfers, trust is paramount. Without maintaining this trust, the entire system risks being compromised. Embracing and integrating advanced technologies is not just about safeguarding funds; it is a crucial step in ensuring the integrity and reliability of the global financial system. Thus, adopting solutions utilizing AI, machine learning, and other state-of-the-art tools, like SEON, represents more than technological progress. More than ever, it's increasingly vital for companies and individuals undertaking this essential process to recognize their role in combating the growing threat of fraud. For more information about SEON, please visit: <https://seon.io/](https://seon.io/) Also published here

Combatting Cross-Border Payment Fraud: A Call to Action for Secure Transactions

Enhancing Cross-Chain Communication The goal of Photon is to solve the issues that are caused by interoperability by enabling decentralized apps (dApps) to communicate with one another in a seamless way across many blockchains. This is true independent of whether or not the blockchains in question are based on Ethereum Virtual Machine (EVM) architectures. This objective is accomplished by the company via the provision of high-speed communications services that connect more than 15 blockchains. Furthermore, the company has aspirations to grow this network even further in the year to come. Introduction to Photon's Cross-Chain Messaging A new breakthrough is likely to make it simpler for decentralized applications (dApps) to communicate with one another across various blockchain networks. This is due to the fact that blockchain technology is always experiencing advancements. Recent experiments have shown that the Photon cross-chain message that Entangle is developing, which will be made available along with the mainnet of Entangle, is the most efficient signaling protocol in the Web3 environment. The company's innovative approach to cross-chain communications was what made this significant improvement in communication possible. It is a new feature known as "transmitter Agents" that is at the heart of the Photon protocol's ability to minimize the amount of time it takes for blocks to be created and to make the transaction process move more smoothly. The Need for Speed and Efficiency There are a plethora of independent networks that make up the world of blockchain technology. Each of these networks operates under its own set of restrictions. The concept that the value of a smart contract is directly proportional to the degree of its communication capabilities is the philosophical foundation upon which Photon's design philosophy is founded. It is very necessary to have effective communication throughout the various chains in order to make full advantage of the potential offered by Web3 technologies. Enhanced user experiences and more decentralized application capabilities will be made possible as a result of this occurrence. Technical Insights The Transmitter Agent framework is responsible for the technological foundations of Photon's high-speed messaging. This framework makes use of a distributed network of agents to identify and propose cross-chain communications in a proactive manner. Through collaborative efforts, these agents are able to reach an agreement on the authenticity of messages, which enables them to swiftly finish transactions that include many chains. In order to maintain a flexible infrastructure that can accommodate the ever-changing nature of blockchain activities, Photon has implemented lightweight off-chain components and decreased the amount of time it takes for blocks to be generated. Furthermore, developers are granted the liberty to design their own unique consensus thresholds, which further optimizes the validation process in order to enable complicated processes and provide a wide range of functionality. Photon's strategy for ensuring fast and reliable transfers is predicated on the optimized design of the Transmitter Agents, which are strategically distributed to facilitate rapid event capture and proposal submission. This design choice allows for quicker consensus among Transmitter Agents and timely execution of cross-chain messages. Overview of Entangle With the goal of creating a data infrastructure that is entirely adaptive and interoperable, Entangle is a larger project that wants to attract both Web3 applications and existing organizations. The instant supply of photon is not the only thing that this effort does. Entangle's goal is to provide blockchain-based applications and ecosystems communication channels for smart contracts that are not only cost-effective but also secure, interoperable, and allow quick transmission. This will be accomplished via the use of Photon as the company's flagship protocol. There are a wide range of real-world data sources that might potentially be affected by such a data solution. These include, but are not limited to, financial markets, digital asset exchanges, sports, gaming, and a great lot of other examples. Through the provision of developers with the capacity to access and interact with a broad variety of permitted data, Entangle is marketing itself as a supplier of complete data solutions in the Web3 area. Entangle is making this effort as part of its overall strategy to strengthen its position in the industry. Conclusion Photon offers fast speeds, freedom, and security, which will help Web3 dApps reach more people and work better. Photon wants to speed up the creation of a blockchain network environment that is more connected and flexible. Entangle wants to make cross-chain DeFi easier and better for all users. This shows that it is committed to making decentralized technology better and easier to use. Adding these kinds of unique rules will change blockchain and the digital market as it grows. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our brand-as-author program. Be it through direct compensation, media partnerships, or networking, the author has a vested interest in the company/ies mentioned in this story. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR

Cross-Chain Communication Hits Lightspeed with Entangle's Photon

This paper is available on arxiv under CC 4.0 license. Authors: (1) Ayei E. Ibor, Trustworthy Digital Infrastructure for Identity Systems, The Alan Turing Institute, United Kingdom; (2) Mark Hooper, Trustworthy Digital Infrastructure for Identity Systems, The Alan Turing Institute, United Kingdom; (3) Carsten Maple, Trustworthy Digital Infrastructure for Identity Systems, The Alan Turing Institute, United Kingdom; (4) Gregory Epiphaniou, WMG, University of Warwick, United Kingdom. Table of Links Abstract & Introduction Background Review of Literature Methodology Discussion of Findings Conclusion and Future Work & References 5. Discussion of Findings The limitations of the current interoperability solutions, that is, eIDAS and X-Road show that there is a plethora of issues and complexities, which are yet to be addressed to achieve interoperability at the foundational level of identity management. Country-specific legislation and vendor-locked systems in developing countries add to these complexities. From the findings, the main limitations of the current interoperability solutions can be summarised as follows: i. Each registry implements its interfaces independently based on the use of a proprietary protocol equivalent to the technology in use. This results in the implementation of new interfaces, sometimes from scratch for new or evolving services. ii. There are different trust levels based on the implemented security architecture for verifying the integrity and authenticity of the data. iii. Incompatible certification authorities arise from different trust levels and legal systems of the trust service providers. iv. Interoperability is based on the signing of bilateral agreements, which are non-trivial and can result in several discrepancies in regulations and policies. v. There is no provision that the network must be accessible to private entities and as such may build inter-government competition on trust services e.g., eIDAS. vi. There is differentiation in notified eID schemes and authentication mechanisms leading to re-identification for public services, healthcare, or financial transactions e.g., eIDAS. These limitations imply that the interoperability of identity systems requires open standards with strong legal, regulatory, and governance structures. Also, there must be mechanisms to mitigate risks to the security and privacy of identification data including consent considerations for data use or sharing by the ID holder as outlined in Alamillo et al. (2023) and Srinivas, Das and Kumar (2019). From the findings, developing countries must also make provisions for a single, consolidated, and standardized view of civil registrations and identification data that constitute a single source of truth. This will enhance the onboarding of citizens and create a robust verification and validation process that does not require several levels of authentication that may increase the overhead of the identity system. Additionally, findings showed that the standardization of the structure and attributes of identity data such as name, date of birth, email, and several other relevant attributes to conform with the W3C recommendation should be a key consideration for interoperability. Enforcing the unicity and singularity of identification data will also ensure that ID holders do not have multiple identities that can hamper interoperability. Similarly, to enable the secure exchange of data or identity assertions, it was also found that developing countries must establish trust relationships through federation protocols that can foster interoperability. Interoperability portrays tremendous benefits to e-Government. We found that interoperability widens the dimensions of e-Government in cross-border identity management and data services. It also helps to provide open and accessible digital public services including systems and processes that allow people to move freely within the developing countries while also utilising public services outside their country of origin. Interoperability also helps to create sustainability, and economies of scale as demonstrated by X-Road and eIDAS (Hoffmann and Solarte-Vasquez, 2022; McBride et al., 2019; Schmidt and Krimmer, 2022). We found that while X-Road provides trustworthy data exchange using security servers that allow its members to communicate directly, it does not perform the verification and validation of the identification data that is part of the data exchange. There are also concerns about the limited amount of notified eID schemes under eIDAS, which builds on the limited scope of the eID schemes and the lack of relevant public services. These concerns underpin the need for the review of these interoperability solutions to underscore the notion of cross-border verification and validation of identification data for seamless data exchange. Building on the evidence from various sources as discussed in the Literature, an architecture for trustworthy cross-border interoperability is proposed in this work. This architecture is represented in Figure 4. From Figure 4, each citizen or prospective ID holder undergoes identity enrolment, which can include civil registration through online or offline capture procedures. The enrolment of the citizen is based on regulations and standards of the foundational identity system of the issuing country represented in Figure 4 as 𝑁𝐼𝐷𝑆௫. At the issuance of the ID credential, the citizen or ID holder presents such a document for establishing and proofing his/her identity to a requesting service provider, identity provider or relying party. Authentication and authorisation services are then used to complete the identity proofing process to allow an ID holder access to a service or resource at the point of access. In a cross-border use case, where a foundational identity system 𝑁𝐼𝐷𝑆௫ communicates with another system, say, in a federated identity ecosystem 𝐹𝑒𝑑ூ஽, or where an ID holder 𝑈ூ஽ requests for a service from the latter, then the processes of verifying and validating the identity of 𝑈ூ஽ should be an integral component of an interoperable identity system unlike in X-Road where such processes are the functions of the service provider/consumer. Verification and validation ensure that the claimed identity is true and belongs to the claimant at the time of the request and throughout service delivery. To achieve this, there is the need to have a trustworthy link that considers the representation of the data, semantics, binding, and the security and privacy of the identification data of 𝑈ூ஽. The relevance of the trust link at the interoperable layer is to ensure that the identity data as well as the requested resource or service maintains its integrity, security, privacy, and confidentiality throughout data exchange. We propose that the representation of the identification data must be data format agnostic as obtainable in X-Road using simple object access protocol (SOAP) and representational state transfer (REST) (Halili and Ramadani, 2018; Krimmer et al., 2021; Priisalu and Ottis, 2017). Also, the representation of credentials on the Web should be in a way that is machineverifiable, private, and cryptographically secure. The semantic interpretation of ID credentials must be unambiguous. That is, verifying credentials and presentations and cryptographically securing them both require predictable, bi-directional, and lossless processes. To be processed in an interoperable manner, any verification of a credential or presentation must be deterministic. The resulting credential or presentation must be semantically and syntactically equivalent to the original construct (Sedlmeir et al., 2021; W3C Recommendation, 2022). Likewise, each verified credential of 𝑈ூ஽ must be bound to its identity to a given level of assurance. This establishes an unbreakable link between the subject (𝑈ூ஽) and the credential to enforce identity disambiguation. Binding is relevant for the verification and validation of the claimed identity at cross-border entry/exit points. Finally, the security and privacy of the identification data are significant as it forms the integral component of the required trustworthiness for interoperability. There are several approaches for implementing the security and privacy of identification data such as the use of Transport Layer Security (TLS), Security Assertion Markup Language (SAML), authentication keys, etc. (for security), secure computation mechanisms, trusted third party, differential privacy, etc. (for privacy) (Grassi, Garcia and Fenton, 2017; Kaaniche, Laurent and Belguith, 2020). We posit that the use of secure computation mechanisms, data minimisation, and differential privacy in a cross-border context can fulfil the required privacy requirements due to the multifaceted risks associated with the exchange of data between interoperating entities. This paper is available on under CC 4.0 license. Arxiv

A Trustworthy Cross-Border Interoperable Identity System: What Our Findings Mean

This paper is available on arxiv under CC 4.0 license. Authors: (1) Ayei E. Ibor, Trustworthy Digital Infrastructure for Identity Systems, The Alan Turing Institute, United Kingdom; (2) Mark Hooper, Trustworthy Digital Infrastructure for Identity Systems, The Alan Turing Institute, United Kingdom; (3) Carsten Maple, Trustworthy Digital Infrastructure for Identity Systems, The Alan Turing Institute, United Kingdom; (4) Gregory Epiphaniou, WMG, University of Warwick, United Kingdom. Table of Links Abstract & Introduction Background Review of Literature Methodology Discussion of Findings Conclusion and Future Work & References 4. Methodology To underscore the importance of interoperability in developing countries, an investigation and comparison of current interoperability solutions in the identity ecosystem was performed. This investigation identified the current limitations of existing solutions and provided the basis for our findings, which are relevant to achieving interoperability for foundational identity systems in developing nations. As a guide, we have presented an approach for the investigation of requirements in Figure 2. The approach in Figure 2 is an easy stepwise guide. The steps include: i) Identify key processes against which baseline requirements should be derived: these processes are already identified in this work. ii) Define common interoperability criteria for eID schemes in candidate countries: this is an important step that must be fulfilled based on the identified key processes of step 1. iii) Baseline requirements against common interoperability criteria, select and compare country-specific eID schemes with current interoperability solutions such as eIDAS and X-Road: this step allows for the identification of common functionalities among eID schemes relative to defined common interoperability criteria. iv) Decide on the benchmarking requirements: it is important to decide on the benchmarking requirements to adequately scope the functional requirements useful for a fully functional interoperable system. v) Use benchmarking requirements against specific eID schemes: using benchmarking requirements against specific eID schemes is useful for identifying missing requirements and functionalities. vi) Identify and scope common functional requirements between eID schemes: this is a significant step that ensures that all requirements for interoperability are adequately captured. vii) Perform requirements gap analysis by identifying missing requirements between eID schemes for all processes defined and recording the differences between eID schemes: the missing requirements must be identified in this step concerning the processes defined in step 1. All significant differences between eID schemes must be recorded (e.g. in Africa and Europe). viii) Define missing capabilities to fulfil newly established requirements: it may be necessary to define missing capabilities in the investigated eID schemes that are relevant to the identified requirements to realise an interoperable identity system. However, this may not be the case where such eID schemes fulfil most of the baseline requirements for interoperability. 4.1 Current Interoperability Solutions For the creation of effective, long-lasting, and usable identity ecosystems, interoperability is essential. Two major interoperability solutions in the identity ecosystem are discussed in this research. These include the Estonian X-Road and the electronic identification and trust services (eIDAS) of the European Union. X-Road is a data exchange layer solution that implements the interoperability of information systems. It allows organisations to exchange data through a secure channel over the Internet. This solution is centrally managed but supports a distributed exchange layer that provides a standardised and secure channel for producing and consuming services (X-Road, 2023a, 2023b). X-Road enhances the confidentiality, integrity, and interoperability between organisations that rely on it for data exchange (Bakhtina et al., 2022; Saputro et al., 2020). Jointly implemented by Estonia and Finland, it has been adopted by several countries and organisations (Saputro et al., 2020). As stated in Solvak et al. (2019), X-Road establishes online connections between service providers and data registries (such as the Population Register, Health Insurance Register, etc.). The citizens who use the X-Road system only give their information to the government once, and the public authority then stores and exchanges the information among itself via the X-Road system (Bhattarai et al., 2019). By signing the messages with the X-Road member's signature key and using a mutually authorised Transport Layer Security (TLS) channel, security servers guarantee the integrity and secrecy of the exchanged messages. By recording the exchanged messages and routinely timestamping the message logs, the signed communications' long-term evidential value is protected. To obtain information on the validity of certificates and timestamp-signed messages, the security servers communicate with trust services. In terms of message exchange, the trust service calls are asynchronous (X-Road, 2023c, 2023d). To exchange messages between a service client and a service provider, three protocols are used. These include X-Road message protocol, X-Road message transport protocol, and OCSP response retrieval protocol (X-Road, 2020). When an interested party such as an organisation joins an X-Road ecosystem, certificates issued by a reputable Certification Authority (CA) are used to verify the identification of each organization and security server. Each security server serves as the technical entry point that manages access control on the organisation level during the data exchange process between registered X-Road members (European Commission, 2023a; X-Road, 2023a). The combination of timestamping and a digital signature ensures that data delivered via X-Road cannot be disputed. On the other hand, eIDAS is a European Union’s framework to ensure that electronic transactions between businesses, citizens, and public agencies are safer and more efficient, regardless of the European country they take place in. It is established by a European Regulation that was implemented in 2014. By introducing a common framework for eID and trust services, the eIDAS regulation makes it easier to supply business services across the EU. It encourages interoperability across the 28 EU nations, making certain that nations mutually recognise each other's electronic identities and trust services across borders (Mocanu et al., 2019). The goal of electronic identification is to completely transform how customers engage with online services. The Member States of the EU may choose to identify citizens electronically. A small number of Member States have created national programs to provide their citizens with electronic identity (eID), with greatly diverse architectures (Lips, Bharosa and Draheim, 2020). National systems, therefore, vary not only in the volume of citizen data they process but also in the degree of data protection they provide to this data. As claimed by Cuijpers and Schroers (2014) and Hölbl, Kežmah and Kompara (2023), businesses and customers can more easily access services or conduct commercial transactions by using electronic identity, or eID, to identify who they are (identification process) and demonstrate that they are who they claim to be (authentication process). Similarly, the regulation stipulates that it will be necessary for all EU nations to accept notified eID systems from other nations by September 2018. When conducting electronic transactions, especially those between firms and clients who are based in another EU country, trust services attempt to improve the trust of EU residents and enterprises (Sharif et al., 2022). The trust services in eIDAS as discussed in ANSSI (2023) and European Commission (2023b) include Electronic Signature (eSignature), Electronic Seal (eSeal), Electronic Timestamp (eTimestamp), Website Authentication Certificates (WACs), and Electronic Registered Delivery Service (eDelivery). eIDAS has been exploited by both the public and private sectors in the EU. Some of the sectors that have benefited from the regulation include the financial services, online retail, transport, and professional services sectors. One of the largest potential beneficiaries of eID and trust services is the financial services industry due to the possibility of enormous commercial opportunities and enhanced cross-border services (Cuijpers and Schroers, 2014; European Commission, 2023b). To meet rising client demand for online services as well as stricter compliance requirements, the identification, authentication, and safeguarding of transactions in the financial services sector are becoming increasingly digitised. 4.2 Comparison of X-Road and eIDAS as Interoperability Solutions The comparison of X-Road and eIDAS is given in Figure 3. This comparison is performed based on identity creation and management, proof of identity, creating and issuing identity credentials, issuing a derived credential, managing the identity credential lifecycle, granting access to an identity holder, data exchange mechanism, security of identification data, and privacy of identification data. This paper is available on under CC 4.0 license. Arxiv

The Methods We Used to Investigate and Compare Cross-Border Interoperable Identity Systems

This paper is available on arxiv under CC 4.0 license. Authors: (1) Ayei E. Ibor, Trustworthy Digital Infrastructure for Identity Systems, The Alan Turing Institute, United Kingdom; (2) Mark Hooper, Trustworthy Digital Infrastructure for Identity Systems, The Alan Turing Institute, United Kingdom; (3) Carsten Maple, Trustworthy Digital Infrastructure for Identity Systems, The Alan Turing Institute, United Kingdom; (4) Gregory Epiphaniou, WMG, University of Warwick, United Kingdom. Table of Links Abstract & Introduction Background Review of Literature Methodology Discussion of Findings Conclusion and Future Work & References 3. Review of Literature Although interoperability has the potential to create a seamless identity ecosystem for data exchange, verification, and validation of digital identities, and expand the reach of national governments for effective service delivery, there are very few research-based approaches for cross-border interoperable identity systems. Backhouse and Halperin (2009) posited that the challenge of establishing interoperable systems is enormous, which does not only consider the technical linking of databases and systems. To this effect, they proposed a three-fold conception of interoperability for identity management systems viz-a-viz technical, legal, and regulatory components to enhance data sharing in the provision of e-government. The factors militating against the full interoperability of federated identity management systems are studied in Catuogno and Galdi (2014). They argued that the tendency for per-site authentication and authorization of ID holders culminates in huge overhead for both the identity/service providers and the ID holders as each site stores different credentials of the user. Therefore, the authors presented Shibboleth as the de facto standard for identity management and point of access to providers of information (PAPI) as a solution that leverages the joining of federations and translation of protocols during cross-federation authentication and authorization (AA) sessions. Sharma and Panigrahi (2015) proposed a roadmap useful to plan and implement the capabilities of interoperability in e-government solutions. The roadmap considered the notion of knowledge sharing among key stakeholders based on vital legal, regulatory, technical, and organisational components that can foster the interoperability of e-government services. One significant limitation of this research is its inability to explore cross-country differences in legislation and regulatory requirements, as it focused only on the inputs from stakeholders in India. Also, Kotzé and Alberts (2017) proposed a baseline conceptual model to achieve an egovernment interoperability framework. The model considered the technical, legislative, social, and political environments of South Africa to serve as a guideline for enterprises that are evolving towards e-governance. Similar studies were carried out by Kanagwa et al. (2018), who investigated the relevance of a national enterprise architecture to support several e-government systems including the systems for the registration of persons in Uganda through semantic interoperability that is achieved based on a set of related ontologies. Still, in both studies, country-specific technical, legislative, social, and political considerations were made, which indicate the absence of cross-border considerations to interoperability, Saputro et al. (2020) discussed the Estonian XRoad as an e-governance solution for secure data exchange and the interoperability of information systems across nine countries. This notwithstanding, this research did not categorise whether the countries investigated are developed or developing to ascertain the level of inclusion or exclusion required for facilitating e-governance. In Hölbl, Kežmah and Kompara (2023), the interoperability and compliance issues in eIDAS are discussed. The authors asserted that eIDAS has limited applicability in the public sector since the regulation does not address new market demands with the added complexity of private online providers connecting to the eIDAS network. Further, the issue of the isolation and inflexibility of notified eID solutions in member states makes it difficult for eIDAS to support a variety of use cases. Domingo and Teevan (2022) discussed the interoperability of cross-border payment solutions to expand trade in Africa. They argued that the success of the African Continental Free Trade Area (AfCFTA) depends largely on the cross-border interoperability of low-value instant payment systems such as mobile money. Consequently, the authors posited that such a policy will enhance inclusion and long-lasting benefits to small-scale businesses. Additionally, Masiero (2023) argued that the effectiveness of digital identity schemes depends on platform features, which must be considered to comprehend the true extent of harm that digital identification might cause due to interoperability. Furthermore, Benaddi et al. (2023) identified the challenges in data sharing and the interoperability of e-government systems. Their focus was on the technical interoperability of e-government entities to enhance collaboration in the use of public data. However, their approach does not consider crossborder perspectives to data sharing including the identification of entities that consume these data. This paper is available on [Arxiv](https://This paper is available on arxiv under CC 4.0 license.) under CC 4.0 license.

A Trustworthy Cross-Border Interoperable Identity System: A Review of the Literature

This paper is available on arxiv under CC 4.0 license. Authors: (1) Ayei E. Ibor, Trustworthy Digital Infrastructure for Identity Systems, The Alan Turing Institute, United Kingdom; (2) Mark Hooper, Trustworthy Digital Infrastructure for Identity Systems, The Alan Turing Institute, United Kingdom; (3) Carsten Maple, Trustworthy Digital Infrastructure for Identity Systems, The Alan Turing Institute, United Kingdom; (4) Gregory Epiphaniou, WMG, University of Warwick, United Kingdom. Table of Links Abstract & Introduction Background Review of Literature Methodology Discussion of Findings Conclusion and Future Work & References 2. Background 2.1 Overview of identity management According to Luong and Park (2023), an identity management system is useful for managing the identity attributes of users. To establish and prove an identity, such identity must first be created through a well-defined registration process. In a foundational identity management system, such a registration process involves the collection, storage, and usage of identity attributes (World Bank Group, 2016). The processes of collecting, storing, and using identity attributes are useful for the verification and validation of ID holders whenever they request services from service providers. Relying parties also depend on these identity attributes to authenticate, authorise, and verify ID holders during transactions or access to a system (Kiourtis et al., 2023). Generally, identification is a key prerequisite for development as it provides the pivot for all categories of transactions and service delivery geared towards inclusive economic growth as summarised in Figure 1. 2.2 Trustworthiness in digital identity management Building robust, secure, and reliable identity management systems is a crucial challenge worldwide. Fathalla et al. (2023) argued that trustworthiness in digital identity management ensures that identification data maintains its integrity, security, privacy, and confidentiality. The consequences of identity fraud or theft are discussed in Hummer and Rebovich (2023); Irvin-Erickson (2023), and Walters (2023). With the increasing rate of attacks on digital identities (Pöhn and Hommel, 2023), privacy concerns are becoming more paramount. To this effect, the use of privacy-preserving technologies that do not reveal the real identities of ID holders is being considered (Luong and Park, 2023; Yin et al., 2022; Tang, Ma, and Cheng, 2023). Typically, a trustworthy system can be relied upon to authenticate and communicate identity attributes without which such information may not be trusted by identity and service providers including relying parties. When an identity system is compromised, it poses a direct threat to the digital identities of ID holders. Significantly, foundational identity systems must be trustworthy since they are part of a nation’s critical infrastructure that contributes to inclusive economic growth and e-Government. 2.3 Requirements for Interoperability To achieve the interoperability of foundational identity systems, requirements must be identified at each stage of the identity management process. In this work, we have identified six processes for scoping requirements to achieve a fully functional interoperable identity system in developing countries. These processes include: i) Identity creation and management ii) Proof of identity iii) Creating and issuing a credential iv) Issuing a derived credential v) Managing the identity credential lifecycle, and vi) Granting access to an ID holder. 2.4 Challenges and opportunities of interoperability in the African identity ecosystem The African identity ecosystem is fragmented with vendor-locked systems that are only accessible within the borders of each country (Gelb and Metz, 2018). One of the challenges of interoperability in this context is the trust issues among African nations including their foundational identity systems (Manda and Backhouse, 2016; Domingo and Teevan, 2022). Trust is a key consideration to interoperability as government-to-citizen, government-togovernment, government to business interactions are performed over the Internet in an interoperable identity ecosystem. Similarly, the increase in the use of vendor-neutral technologies for the verification and validation of ID holders at cross-border points is envisaged to introduce more security and privacy concerns. Moreover, cross-border digital trust requires a secure and reliable environment. Connecting identity systems can create more complex environments for conducting digital transactions and interactions across the continent (African Union, 2020). Challenges in infrastructure, and disparities in social structures, norms, and behaviour, also affect the perception of privacy, security, and trust by stakeholders. Other challenges include advancements in cutting-edge technology that change how personal data is gathered and analysed from various, unrelated sources including consent management for data sharing, the reluctance of various governments to invest in privacy-enhancing technologies, streamline security policies and legislation, and establish new acts for the protection of the privacy and confidentiality of identification data. Conversely, there are several opportunities for interoperability as it promotes vendor neutrality using common standards in an identity ecosystem. In the same sense, interoperability enforces data integrity by ensuring that each identity system provides a single source of truth for identification data and reduces identity fraud for e-Government services (The World Bank, 2023b; Domingo and Teevan, 2022). With an interoperable continent-wide identity ecosystem, new markets, digital services, and applications are possible, thus enabling innovation and new use cases to widen the dimensions of e-Government. This paper is available on under CC 4.0 license. Arxiv

Cross-Border Interoperable Identity System for Developing Countries: What You Need to Know

This paper is available on arxiv under CC 4.0 license. Authors: (1) Ayei E. Ibor, Trustworthy Digital Infrastructure for Identity Systems, The Alan Turing Institute, United Kingdom; (2) Mark Hooper, Trustworthy Digital Infrastructure for Identity Systems, The Alan Turing Institute, United Kingdom; (3) Carsten Maple, Trustworthy Digital Infrastructure for Identity Systems, The Alan Turing Institute, United Kingdom; (4) Gregory Epiphaniou, WMG, University of Warwick, United Kingdom. Table of Links Abstract & Introduction Background Review of Literature Methodology Discussion of Findings Conclusion and Future Work & References Abstract Foundational identity systems (FIDS) have been used to optimise service delivery and inclusive economic growth in developing countries. As developing nations increasingly seek to use FIDS for the identification and authentication of identity (ID) holders, trustworthy interoperability will help to develop a cross-border dimension of e-Government. Despite this potential, there has not been any significant research on the interoperability of FIDS in the African identity ecosystem. There are several challenges to this; on one hand, complex internal political dynamics have resulted in weak institutions, implying that FIDS could be exploited for political gains. On the other hand, the trust in the government by the citizens or identity holders is habitually low, in which case, data security and privacy protection concerns become paramount. In the same sense, some FIDS are technology-locked, thus interoperability is primarily ambiguous. There are also issues of cross-system compatibility, legislation, vendor-locked system design principles and unclear regulatory provisions for data sharing. Fundamentally, interoperability is an essential prerequisite for e-Government services and underpins optimal service delivery in education, social security, and financial services including gender and equality as already demonstrated by the European Union. Furthermore, cohesive data exchange through an interoperable identity system will create an ecosystem of efficient data governance and the integration of cross-border FIDS. Consequently, this research will seek to identify the challenges, opportunities, and requirements for cross-border interoperability in an African context. Our findings show that interoperability in the African identity ecosystem is vital to strengthen the seamless authentication and verification of identity holders for inclusive economic growth and widen the dimensions of e-Government across the continent. Keywords: cross-border interoperability, digital identity, trustworthiness, e-Government 1. Introduction One of the Sustainable Development Goals (SDGs) of the United Nations is to provide legal identity for all citizens, which also includes birth registration by 2030 (World Bank Group, 2018). Primarily, identification allows individuals to exercise their rights to be identified and legally recognised while the government and private sector depend on it for effective service delivery. In this sense, a national identity system is crucial to the identification and authentication of natural or legal persons and provides a means for citizens to access critical services including participation in formal political, social, and economic life (Gelb and Metz, 2018). Achieving sustainable development is a key consideration of most national governments and forms the basis for inclusive and responsible identification schemes at the foundational level. Fundamentally, national identification schemes are the pivot for social security, immigration, financial and economic inclusion, healthcare, voting, gender equality, transportation, and education (Colbern and Ramakrishnan, 2018). Consequently, identity management plays a key role in promoting e-government by bringing services closer to the people. Modern identification systems are robust tools for the delivery of transparent administration, reduction in fraud and leakages for social benefits, providing adequate security for the citizens, extracting accurate biographic data for effective economic planning, and responding to natural disasters (Atick, 2016). These seeming benefits are yet to solve the identification crisis in most developing nations as about 850 million people across the globe are yet to have access to a valid identity credential, mostly in sub-Saharan Africa and South Asia (The World Bank, 2023a). According to the World Bank Identification for Development (ID4D) dataset (The World Bank, 2023a), most people without official identification are residents of low-income countries. These sets of persons also include marginalised and vulnerable groups consisting of children, whose births were not documented in the civil registry of the affected country, women in rural areas with no access to digital services, and adults below the age of 25 years. Particularly, digital identification systems can improve how the public and commercial sectors provide services and lay the groundwork for new markets, services, and systems, such as egovernment, cashless transactions, and the digital economy. Identification systems must, however, have high levels of coverage and inclusion within the population, be resilient to fraud and error, operate within a governance framework that protects personal data, fosters trust and accountability, and facilitates end-user control to fulfil their potential for facilitating sustainable development and increasing public sector efficiency (African Union, 2020; Bandura and Ramanujam, 2021). There is a growing demand for digital identity to be mutually recognised and portable between countries in the modern digital age through an interoperability framework and in the context of regional and global integration and migration, which can be facilitated through trust and standards. Interoperability, in this context, refers to the ability of disparate foundational identity systems to exchange data through seamless communication of identification and authentication information. These exchanges must be trustworthy or inherently secure, available, and reliable. Although there are complex internal political dynamics in most developing countries that result in weak institutions, and the lack of trust in government by the citizens including the notion of security and privacy protection concerns, legislation, cross-system compatibility, vendor-locked system design principles and unclear regulatory provisions for data sharing, our findings show that interoperability is vital to widen the dimensions of e-Government. In this paper, the challenges, opportunities, and requirements for trustworthy cross-border interoperability are discussed. The rest of the paper is organised as follows; in Section 2, the background to the study is given while in Section 3, a review of literature is discussed. Section 4 presents the methodology of the research. In Section 5, the discussion of findings is presented, and the conclusion and future work is given in Section 6. This paper is available on under CC 4.0 license. Arxiv

A Trustworthy Cross-Border Interoperable Identity System for Developing Countries: The Beginning

2024 is touted as the “The Ultimate Election Year” by Time magazine and rightfully so as more than 50 countries prepare for national elections, roughly more than half the population of the planet. Some of the largest democracies up for elections from the stated list are India, the US, Mexico, Indonesia, and more, making 2024 a turning point in the geopolitical landscape for democracy. Media is the fourth pillar of with the responsibility of upholding the truth to the public, but a closer look at the current scenario would show you a different perspective. There is no one sinister plot at play, it is a series of unfortunate events catalyzed by well intentioned citizens misplacing their enthusiasm to further the misinformation chaos. democracy Systematic erosion of democracy may now be a field day with the advent of AI, specifically massification of it through Generative AI Systematic erosion of democracy may now be a field day with the advent of AI, specifically massification of it through . For instance, , an organization that tracks misinformation, just since May 2023, websites hosting AI-created false articles have increased by more than 1,000%, ballooning from 49 sites to more than 600. Propaganda operations that were usually menial tasks performed by underpaid cyber armies are now easily enabled by AI that is strikingly similar to official news. The lines of real and fake are easily blurred, even for the well informed and well read consumers and this freefall of misinformation may lead us soon to question the nature of news altogether. Generative AI according to NewsGuard In Here, Lies the Opportunity If AI is the poison that contaminates the well of information, it is also the said antidote, or at least a key ingredient. The technology can also be deployed to detect misinformation and text generated by AI and also launching counter to contain the spread of misinformation. campaigns Even tech companies are huddling to create proactive solutions to mitigate the risks. Industry leaders, including OpenAI, Microsoft, TikTok, X, Meta, Amazon, and Google, disclosed a new agreement, ‘ ’, that aims to minimize the risk of AI interfering in the 2024 US elections. They have pledged a series of commitments that include developing new technologies to mitigate risks, detecting distribution on their platforms, more transparency and launching public awareness campaigns on media literacy. Tech Accord to Combat Deceptive Use of AI in 2024 Elections However, this is mostly focused on the US elections, and as important as they may be, media literacy is a much bigger issue in the developing countries. An independent alternative powered by the honchos of the media industry could be a viable solution. It is an opportunity in disguise where the whole industry can unite to fight this deviant and also create a wholesome database of accurate news links. This also creates an easy access for the user to consume news of their preferred news networks while comparing the headlines. If not through an industry initiative, but with help of veteran experts this is an achievable task. An unimpeachable mecca of news, the ultimate utopia or rather resetting to the original DD news in India or PBS in US days, no nonsense shows, just news. In fact, the silent period rule in large scale democracies like ours, could be even extended from 48 hours to 6 months as public perception is moulded constantly with accessibility of news on their phones and these laws predate the notification technology. When it comes to AI, this is still a manageable expectation, for instance Midjourney’s CEO, David Holz was considering banning creation of political (in context of the US elections) images for 2024. If there are guardrails installed on the creation process by AI companies, it is a beast that can be possibly tamed. This article was originally published by on Sanjay Sehgal The Tech Panda.

The Influence of AI on Voter Decision-Making: A Global Democracy’s Crossroads

Browser compatibility is a term that refers to the ability of a specific website and application to be fully functional on different browsers. In this modern digital world, businesses rely heavily on their online presence to attract and retain customers, so websites should be accessible across different devices and browsers to ensure a seamless user experience. Different browsers should be compatible with the website’s HTML, CSS, and JavaScript. In this article, we’ll discuss the importance of cross-browser compatibility, exploring the common issues, best practices, and emerging trends in this field. What Is Browser Compatibility Testing Browser compatibility testing is a type of non-functional testing that ensures that all functions are working properly on different browsers, like Microsoft Edge, Google Chrome, Safari, etc. As all browsers have their own configuration and code interpretation, browser compatibility ensures application uniformity. However, due to compatibility issues, websites may react differently on different browsers and at this point, testing of the browser compatibility takes a crucial role to ensure flawless user experience. How Browser Compatibility Works? There are multiple web browsers available in the market and each of them has its rendering engine and interpretation of web technologies, ensuring that your web browser works consistently across them can be a complex task. This can be done by using , which are agreed-upon guidelines for how web pages should be coded. web standards When a browser encounters a web page that is coded according to web standards, it should be able to render the page correctly, regardless of the browser’s implementation of those standards. Each browser has its own rendering engine, which interprets , , and code and renders it into a visual representation that users can interact with. For example, Google Chrome uses Blink, Mozilla Firefox uses Gecko, while Safari uses WebKit. HTML CSS JavaScript To ensure cross-browser compatibility, web developers and designers must test their websites across different browsers to identify and fix any discrepancies or bugs. They can also use tools and frameworks that help streamline the process of testing and ensuring compatibility across different browsers. Common Cross-Browser Compatibility Issues To Avoid? To ensure a smooth cross-browser experience, you need to know about the most common cross-browser compatibility issues related to the development. Different browsers take CSS rules differently. It leads to an inconsistent layout, unnecessary spaces, and front rendering. To avoid these types of glitches, developers need to rely on the standard CSS-compliant for a consistent rendering. Different CSS rendering: The behavior of JavaScript may vary across different browsers. Even today, some of the latest JavaScript features are not supported by older browsers or require polyfills or transpilers to work. Compatibility with JavaScript: Sometimes, many browsers do not support the latest HTML5 and CSS3 features. Using unsupported features can result in broken layouts or missing functionality in certain browsers. To prevent this, research and understand which HTML5 and CSS3 features are supported in your target browsers. Bypass the unsupported HTML5 and CSS3 features: Mobile browsers handle touch and gesture events differently, which can impact the usability of touch-friendly websites. Touch and gesture issues: Some browsers may contain some bugs which can create a major fault in the future. So, it is really important to remove those bugs to sustain the best user experience. Browser-specific bugs: Best Practices To Achieve Cross-Browser Compatibility The main goal of cross-browser compatibility testing is to mark and address the bugs and errors when users visit your website from different applications.  It is crucial to ensure that your website or web application functions correctly and appears consistently across different web browsers and versions. Here are some key considerations: You need to identify the targeted browser versions by considering their working on different devices and platforms. You also need to create a matrix to list all the targeted browsers and their various versions that your target audience is likely to use. Define the browser and device matrix: Using a framework to encapsulate your code is a great way to start developing a website. Frameworks provide many advantages, including being optimized for cross-browser issues and automatically creating responsive elements. By using a framework, developers can focus on the functionalities while leaving the cross-browser compatibility issues to the framework. Framework encapsulation: Automation testing tools like Selenium, Cypress, and TestGrid can significantly speed up the cross-browser compatibility testing process. These tools test the websites across various browsers simultaneously without the need for manual intervention. Using automation testing tools: This step deals with the W3C standards. A well-validated code makes the website compatible and minimizes the risk of issues arising due to syntax errors or non-standard practices. Develop a channel for code validation: Adding a retest and regression testing channel helps the development to fix the compatibility issues. Whenever changes or updates are introduced, retesting the website across the defined browser and device matrix helps to identify and address any potential compatibility problems early on. Retest and regression: Set up some feedback loops to ensure that your website works well across different browsers and devices. Encourage user feedback through a “Report a Bug” button and respond promptly to user reports. User feedback acts as a real-world validation mechanism, helping you identify and rectify hidden compatibility challenges. Set up some feedback loops: Conclusion As the digital world evolves and updates continuously, with new versions and devices becoming outdated, cross-browser testing is essential to ensure that websites and web applications work as intended for all users. Here in this article today, we have learned about browser compatibility and its importance with the issues related to it. Cross-browser compatibility is an ongoing challenge, but with the right approach and best practices, we can make it more diverse and dynamic in the future.

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