Medialab

I walked into Regina Pizzeria slightly late on Sunday night. It was my first time in Massachusetts — my first time on the east coast, in fact — and I wanted to take advantage of the two hours between my flight landing and dinnertime to explore the city.

A Week at the MIT Media Lab, A Lifetime of Impact

Vana Mainnet Goes Live With $VANA To Power Data As a New Asset Class In Global AI Economy

This portion adheres to ethical guidelines, protects privacy, and ensures data reproducibility while analyzing QAnon authorship with public materials.

Ethical Considerations in QAnon Authorship Attribution Research

Using rolling stylometry and machine learning to analyze QAnon texts, identifying stylistic shifts and attributing authorship through linguistic features.

Rolling Stylometry and Machine Learning Analyzes  QAnon Texts Patterns

This section tackles the challenges of attributing authorship to Q drops, a unique genre with distinct linguistic features that complicate traditional analysis.

Analyzing QDrops Texts shows Distinct Linguistic Features than Traditional Ones

This section addresses imbalanced datasets and generic differences in QAnon text analysis, creating large and controlled subcorpora for machine-learning models.

QAnon Text Analysis shows Imbalanced Datasets and Generic differences

This section employs algorithms to detect and remove shared quotations in QAnon texts, mitigating biases and ensuring accurate authorship profiling.

Addressing Quotations and Copy-Paste in QAnon Authorship Attribution

This section highlights the challenges of building a reliable text corpus for QAnon authorship analysis due to deleted accounts and limited archival data.

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