WiDS Maastricht 2021 - Anda Iamnitchi

Modeling Multi-Platform Information Diffusion in Social Media: Data-Driven Observations

Accurately modeling information diffusion within and across social media platforms has many practical applications, such as estimating the size of the audience exposed to a particular narrative or developing intervention techniques for addressing misinformation. At the same time, advances in machine learning techniques and the availability of large collections of social media datasets promise significant advances in understanding how to model user activities and user interactions on these platforms. Yet real data reveal phenomena that pose significant challenges to modeling: events in the physical world affect in varying ways conversations on different social media platforms; coordinated influence campaigns may swing discussions in unexpected directions; a platform’s algorithms direct who sees which message.  This key talk discussed the challenges encountered in modeling social media activity in various contexts, from announcements of software vulnerabilities to online reactions during political crises. 

You can view the presentation here.

_{Prof. Dr. Adriana Iamnitchi is Professor of Computer Science and Engineering at the University of South Florida. She holds a PhD in Computer Science from The University of Chicago. Her research lies at the intersection of distributed systems, social computing, empirical analysis of phenomena in online social environments and designing solutions for modeling them.}