Invited Speaker---Assoc. Prof. Shieu-Hong Lin


Mathematics / Computer Science Department, Biola University, USA

Biography: Dr. Shieu-Hong Lin received his Ph.D. in Computer Science from Brown University in 1997 and is a Professor of Mathematics and Computer Science at Biola University, Los Angeles, USA. His research interests include algorithms, artificial intelligence, automatic reasoning and formal verification, combinatorial optimization, data mining and machine learning. He has published many articles in journals and conference proceedings in these research areas.

Speech Title: Web Mining on Political Homophily in Twitter Communities
Abstract: Homophily is the phenomenon that people who are similar in some aspect interact at a significantly higher rate. We developed a web mining framework using Twitter's application programming interface to investigate political homophily in online Twitter communities. First, we conducted research regarding the nature of Twitter communications among active members of the US congress. Our findings showed strong evidence of homophily with respect to party affiliation and a significant higher rate of communication for members in the same party. In an entirely distinct differentiation, we discovered moderate evidence of inverse homophily with respect to seniority and a significant higher rate of communication between members at different seniority levels. Second, we used the web mining framework to identify common Twitter followers between pairs of top news sites in US. We utilized the data as homophily indicators for measuring similarity among news sites to look into the political spectrum of news sites.