[PAST EVENT] Decoding Human Behavior for Social Media
Speaker: Tianran Hu, University of Rochester
Title: Decoding Human Behavior for Social Media
Abstract: Given its large user base, deep user engagement level, and comprehensive coverage on various human activities, social media offers us a novel and effective lens for observing, monitoring, analyzing, and understanding human behavior. In this talk, I will discuss my work on decoding human behavior at both individual and collective levels using social media data from two perspectives: mobility and language. Through the lens of mobility, I will present our analogy between human activities across online communities and movements in the physical world. The analogy leads us to a series of findings on the striking similarities between physical and cyber spaces, and reveals promising new research directions. Through the lens of language, our work investigates how people's social identities affect their language use. I will also introduce our work on the use of nonverbal cues in Computer-Mediated Communication (CMC) -- emoji.
Bio: Tianran Hu is a Ph.D. candidate in Computer Science at the University of Rochester. His work focuses on studying human behavior, including understanding human mobility patterns, online activities, and language usage. During his Ph.D. study, Tianran has interned at Tencent AI Lab, IBM Research Almaden, Microsoft Research Asia, and Palo Alto Research Center. More information is available at http://www.cs.rochester.edu/u/thu/