Talk on POINT PROCESS ON SOCIAL ANALYSIS  by Dr.Srijith. P.K, Assistant  Professor, Dept. of CSE , IIT Hyderabad 

Point Processes for Social Network Analysis.

Abstract

The users in online social networks generate information which propagates across the network resulting in information cascades. I will talk about  modelling the evolution of information cascades in Twitter using the framework of Hawkes process. Hawkes process is a self exciting point process useful for modelling the temporal dynamics in Twitter. We developed various Hawkes process models which consider properties specific to Twitter such as the conversational structure, network information and user features.  The effectiveness of  the Hawkes process models is demonstrated on real world Twitter datasets.  I will also talk about the  problem  of stance classification of posts in social networks.  We treat the problem as time sensitive sequence classification and develop a Hawkes process model which can effectively address this task. The usefulness of the model is demonstrated on  the problem of rumour stance classification in Twitter.
 

Profile of the speaker

Dr. P. K. Srijith is an Assistant Professor at the department of Computer Science and Engineering, IIT Hyderabad. Previously, he worked as post-doctoral researcher at the University of Melbourne and the University of Sheffield. He did his Ph.D. at the department of Computer Science and Automation, Indian Institute of Science. He is interested in developing Bayesian non-parametric and probabilistic machine learning models to solve real world problems arising in the various domains of data science such as social networks, healthcare,  and astrophysics.