Enhancing User Protection with Optimal Prebunking in Social Networks

Author: (1) Yigit Ege Bayiz, Electrical and Computer Engineering The University of Texas at Austin Austin, Texas, USA (Email: egebayiz@utexas.edu); (2) Ufuk Topcu, Aerospace Engineering and Engineering Mechanics The University of Texas at Austin Austin, Texas, USA (Email: utopcu@utexas.edu). Table of Links Abstract and Introduction Related Works Preliminaries Optimal Prebunking Problem Deterministic Baseline Policies Temporally Equidistant Prebunking Numerical Results Conclusion and References IV. OPTIMAL PREBUNKING PROBLEM To guard user c against misinformation, we employ prebunking. Prebunking relies on inoculating the users in the network by providing the users with correct information before they encounter a misinformation that contradicts the correct information. The idea of prebunking is similar to that of vaccination, where an early intervention to misinformation can immunize some users against it, reducing misinformation spread in the population. Fig. 1 shows the effect of prebunking in a small network of users. Lastly, we note that it is impossible to guard the center user c against a cascading misinformation k if the misinformation starts from c. As there is no way of estimating when a new misinformation cascade will start, there is no way to preemptively provide a prebunk to the central user c if a misinformation cascade starts on it. Thus, for theoretical analysis it is often necessary to assume that a misinformation cascade never starts at c. We rephrase this assumption as follows: This paper is available on arxiv under CC 4.0 license. Author: (1) Yigit Ege Bayiz, Electrical and Computer Engineering The University of Texas at Austin Austin, Texas, USA (Email: egebayiz@utexas.edu); (2) Ufuk Topcu, Aerospace Engineering and Engineering Mechanics The University of Texas at Austin Austin, Texas, USA (Email: utopcu@utexas.edu). Author: Author: (1) Yigit Ege Bayiz, Electrical and Computer Engineering The University of Texas at Austin Austin, Texas, USA (Email: egebayiz@utexas.edu); (2) Ufuk Topcu, Aerospace Engineering and Engineering Mechanics The University of Texas at Austin Austin, Texas, USA (Email: utopcu@utexas.edu). Table of Links Abstract and Introduction Abstract and Introduction Related Works Related Works Preliminaries Preliminaries Optimal Prebunking Problem Optimal Prebunking Problem Deterministic Baseline Policies Deterministic Baseline Policies Temporally Equidistant Prebunking Temporally Equidistant Prebunking Numerical Results Numerical Results Conclusion and References Conclusion and References IV. OPTIMAL PREBUNKING PROBLEM To guard user c against misinformation, we employ prebunking. Prebunking relies on inoculating the users in the network by providing the users with correct information before they encounter a misinformation that contradicts the correct information. The idea of prebunking is similar to that of vaccination, where an early intervention to misinformation can immunize some users against it, reducing misinformation spread in the population. Fig. 1 shows the effect of prebunking in a small network of users. Lastly, we note that it is impossible to guard the center user c against a cascading misinformation k if the misinformation starts from c. As there is no way of estimating when a new misinformation cascade will start, there is no way to preemptively provide a prebunk to the central user c if a misinformation cascade starts on it. Thus, for theoretical analysis it is often necessary to assume that a misinformation cascade never starts at c. We rephrase this assumption as follows: This paper is available on arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. available on arxiv