Dissertation Proposal - Royal Pathak

Enhancing Interventions Against Misinformation Propagation in Social Networks

Presented by Royal Pathak, Computer Science emphasis
Via Zoom

Abstract

Social networks serve as platforms for interaction, information sharing, advertising, and influencing opinions. Despite their advantages, they are recognized for spreading misinformation, potentially exacerbated by biased recommendation algorithms (\textbf{RAs}). This proposal aims to proactively enhance intervention against misinformation by outlining three objectives. In first objective, we investigate how RAs could contribute to misinformation recommendation and propagation in social networks and propose a \emph{new} framework to measure the impacts of RAs on misinformation diffusion. The framework considers both user and RA behavior–to study and quantify the impact of RAs in spreading misinformation. We also defined a novel information diffusion model that incorporates network, news and user features. The second objective involves examining misinformation intervention practices, ranging from fake news detection and its outright removal to intervention methods within the realm of social sciences. We contribute further by studying theoretical intervention frameworks in social science to address the issue of misinformation amplification caused by RAs, proposing a novel information diffusion model. The third objective is to develop a recommender system prioritizing the integration of factors such as diversity, trustworthy network and trustworthy neighbors while considering user-item latent factors. The achievement of these objectives will enhance the intervention against misinformation propagation and bring significant implications for social scientists in shaping a more resilient and informed cyberspace.

Committee

Dr. Francesca Spezzano (Chair), Dr. Edoardo Serra, Dr. Nasir Eisty