EBSIS Summer School
on Distributed Event Based Systems
and Related Topics 2017

July 10—14, 2017 – Timmendorfer Strand, Germany

★ Lecture Abstract

Analyzing Information Diffusion in Social Media

Peter Fischer (University of Freiburg)

Modern social media like Twitter or Facebook encompass a significant and growing share of the population, which is actively using it to share messages. Given this broad coverage of the world as well as its fast reaction times, social media acts as a powerful social sensor, while activities originating on social media can also have significant impact on the physical world. Information Diffusion, describing where and by whom a particular piece of information has been created, how it has been propagated and whom it may have influenced, has recently gathered considerable interest in research and practice. Analyses of information diffusion can (for example) be applied to assess the relevance and truthfulness of messages in social media, given the current media frenzy on fake news). Yet, most of the research on information diffusion is centered on complex models with offline computations, making them unsuitable for real-time, large-scale analyses. Our ongoing work focuses on developing algorithms and systems to trace and analyze the spreading of information in social media that produce large scale, rapid data. In order to do so, several technical challenges need to be addressed, among them applying iterative algorithms on high-volume/high-speed streams and low-latency access to very large graphs.

Speaker Bio

Peter M. Fischer is an assistant professor (Juniorprofessor) for Web Science at University of Freiburg, CS Department. Before that, he was a senior researcher at ETH Zurich. He holds a PhD from ETH Zurich and an MSc/Diploma from TU Munich, both in Computer Science. His current research interests include analysis and management of large-scale, evolving data, in particular social media analysis, contextualization of information and temporal data management.