PhD Dissertation Defense by Roy LEE Ka Wei | Analyzing and Modeling Users in Multiple Online Social Platforms

Online social platforms (OSPs), such as Facebook, Twitter, and Instagram, have grown monumentally over recent years. It was reported that as of August 2017, Facebook has over 2 billion monthly active users, while Instagram and Twitter have over 700 million and 300 million monthly active user accounts respectively.

The vast amount of user-generated content and social data gathered in these behemoth platforms have made them rich data sources for academic and industrial research. However many of the existing research work has focused on analyzing and modeling users behaviors in a single platform setting, neglecting the inter-dependencies of user behaviors across multiple OSPs. In this dissertation, I will present my work on analyzing and modeling user behaviors in multiple OSPs. In particular, I will focus on (i) analyzing users' topical interests and platform preferences across multiple OSPs, and (ii) modeling influential users in multiple OSPs.

Roy Ka Wei Lee is a Ph.D. candidate in School of Information Systems, Singapore Management University, advised by Professor Lim Ee-Peng. He received his Bachelor of Science (IS Management) and Master of Applied Information System from Singapore Management University. His work lies in the intersection of data science and social computing. In particular, He is interested in studying user behaviors and information diffusion across multiple social networks. Concurrent with his Ph.D. studies, he is also a Research Engineer at Living Analytics Research Centre (LARC).