Media events" such as political debates generate conditions of shared attention as many users simultaneously tune in with the dual screens of broadcast and social media to view and participate. Are collective patterns of user behavior under conditions of shared attention distinct from other "bursts" of activity like breaking news events? Using data from a population of approximately 200,000 politically-active Twitter users, we compare features of their behavior during eight major events during the 2012 U.S. presidential election to examine (1) the impact of "media events" have on patterns of social media use compared to "typical" time and (2) whether changes during media events are attributable to changes in behavior across the entire population or an artifact of changes in elite users' behavior. Our findings suggest that while this population became more active during media events, this additional activity reflects concentrated attention to a handful of users, hashtags, and tweets.
Yu-Ru Lin is currently 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 for studying human and social dynamics. She has been using massive social media data and anonymized cellphone records (CDRs) to understand the societal responses with respect to political events and under exogenous shocks such as emergencies.
Faculty Host: Brad Myers