Speaker: Qiaozhu Mei, School of Information, University of Michigan
Title: The Foreseer: Integrative Retrieval and Mining of information in Online Communities
Room: Informatics West 105
Abstract: With the growth of online communities, the Web has evolved from networks of shared documents to networks of knowledge-sharing groups and individuals. A vast amount of heterogeneous yet interrelated information is being generated for which existing information analysis techniques are inadequate. Current tools often neglect the actual creators and consumers of information, and as a result, the findings are only useful to data analysts. The user-centric Foreseer is the next generation of information analysis for online communities. It represents a new paradigm of study through the four “C’s”: content, context, crowd, and cloud. Information analysis of content is put into the context of the users’ daily lives to benefit the communities (crowd) that generate information residing in the cloud.
In this talk, we will introduce our recent effort of integrative information analysis of online communities. We will highlight the real world problems in online communities to which the Foreseer techniques have been successfully applied. These topics include tracking event evolution and diffusion, detecting misinformation, predicting the adoption of hashtags in microblogging communities, and the prediction of user behaviors in microfinance communities.
Bio: Qiaozhu Mei is an Assistant Professor at the School of Information, the University of Michigan. He received his PhD from the University of Illinois at Urbana-Champaign. He is widely interested in information retrieval, text mining, natural language processing and their applications in web search, social computing, and health informatics. He has served in the program committee of almost all major conferences in these areas. He is also a recipient of the NSF CAREER Award.