| about | research | teaching | publications | cv |
YU-RU LINAssistant Professor
Office: Phone: 412-624-9470 Email: yurulin (at) pitt.edu |
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about
I am an assistant professor at School of Information Sciences, University of Pittsburgh. In the past, I have worked as an assistant research professor at the College of Social Sciences and Humanities, Northeastern University. I have also been a postdoctoral research fellow at the Institute for Quantitative Social Science, Harvard University and College of Computer and Information Science, Northeastern University.
I am interested in studying social and political networks, as well as computational and visualization methods for understanding network data. My work has focused on large-scale community dynamics, rich-context (high-dimensional) social information summarization and representation. I have been using massive social media data and anonymized cellphone records (CDRs) to understand the collective responses with respect to political events and under exogenous shocks such as emergencies.
I am a computer scientist by training, and I identify myself as a computational social scientist as I concern more with questions like: "how would a society be informed?" "how do people share information, ideas and opinions in various contexts?" These questions have led me to explore analytical and computational techniques for mining heterogeneous, multi-relational, and semistructured data that can advance our understanding about structures in networked societies.
During my postdoctoral training, I have worked with colleagues from the disciplines of Physics and Social Sciences in the BarabasiLab and the LazerLab, where I worked with Dr. David Lazer. I received my Ph.D. in Computer Science from Arizona State University, with an interdisciplinary concentration in Arts Media and Engineering, where I worked with Dr. Hari Sundaram and Dr. Aisling Kelliher. My Ph.D. work focused on extracting human communities that collaborate around certain topics or shared media artifacts. I have proposed matrix and tensor based techniques for analyzing community structures and evolutions in time-varying heterogeneous social networks, and developed visualizations to support community discovery in the context of everyday social media use.
research highlights
My publications and talk slides can be downloaded here.03/2014 Paper accepted to be published in PLoS ONE: "Rising Tides or Rising Stars?: Dynamics of Shared Attention on Twitter During Media Events". This article presents new and detailed empirical findings about how the social dynamics of online social interactions and information sharing temporarily but fundamentally change in response to external events.11/2013 Paper "Why so Similar?: Identifying Semantic Organizing Processes in Large Textual Corpora" makes SSRN's Top Ten list.04/2013 I am co-chairing 2013 KDD Mutimedia Data Mining Workshop, which will be held in conjunction with KDD 2013. The theme of this year is "mining large-scale rich content in a networked society." We look forward to your participation!03/2013 Paper accepted in ICWSM 2013: "#Bigbirds Never Die: Understanding Social Dynamics of Emergent Hashtags." This is the first study on the lifecycle of hashtag adoption and use in response to exogenous shocks.02/2013 Paper accepted in WWW 2013: "Voices of Victory: A Computational Focus Group Framework for Tracking Opinion Shift in Real Time" (P&E Track). The work was featured in news@Northeaster during the election. Check out the recap for the US presidential debates.07/2012 Paper accepted in InfoVis 2012: "Whisper: Tracing the Spatiotemporal Process of Information Diffusion in Real Time." It was featured in Information Aesthetic. Check out the demo video.05/2012 Paper published in PLoS ONE:"Mesoscopic Structure and Social Aspects of Human Mobility". In the paper we discovered a universal "habitat" structure from spatiotemporal flows of human mobility, with temporal scaling patterns distinct from all previous observations and unpredicted by current models.04/2012 Paper accepted in Web Science 2012: "Recipe recommendation using ingredient networks". It was featured in Science News, techology review and NPR Blog.
teaching & tutorials
Fall 2013 Data Mining07/2012 Network visualization and research methodology, 2012 Summer Dissertation Workshop in World History, July 26 and 27.06/2012 Network Visualization at the Northeastern/MIT/Harvard Computational Social Science 2012 Workshop. The tutorial materials are available at the workshop wiki. See visualization examples created by the workshop participants.