Institute of Information Science, Academia Sinica

In this talk, I will present a study that utilizes big data to examine urban encounters and the dynamics of emotional spreading during a recent mass violence event. The 2013 Boston Marathon bombing presents a rare opportunity to study how a disruptive event can trigger inter-communal emotions and expressions -- where members of one community express feelings about and support for members of a distant community.  We use over 180 million geocoded tweets over an entire month to study how Twitter users from different cities expressed three different emotions: fear, sympathy and solidarity, in reaction to the bombings. We capture spikes in fear in different cities by using sentiment and time-series analyses, and track expressions of comfort and solidarity based on the emergent use of hashtags widely adopted after the bombings. Analyses show that the extent to which residents of a city visit Boston is the best predictor of fear and solidarity expression, as well as a strong predictor of the expression of comfort.  The expression of fear is also directly related to the expression of comfort. Our study has theoretical implications regarding the diffusion of information and emotional contagion as well as practical implications for understanding how important information and social support can be effectively collected and distributed to populations in need. 

Yu-Ru Lin is an assistant professor at the School of Information Sciences, University of Pittsburgh. Her research interests include human mobility, social and political network dynamics, and computational social science. She has developed computational approaches for mining and visualizing large-scale, time-varying, heterogeneous, multi-relational, and semi-structured data. Her current research focuses on extracting system-level features from big data sets, including social media data and anonymized cellphone records, for studying human and social dynamics, particularly under exogenous events such as emergencies and media events. Her work has appeared in prestigious scientific venues including WWW, SIGKDD, InfoVis, ACM TKDD, ACM TOMCCAP, IEEEP, PLoS ONE and Data Science. Her research vision is to use big data in the service of humanity, through developing new methodologies to collect, mine and utilize information to support collective sensemaking in real time. Additional information on Dr. Lin may be found at: http://www.yurulin.com/