Information Seeking and Responding Networks in Physical Gatherings: A Case Study of Academic Conferences in Twitter

With the allure of immediacy, social media like Twitter have been widely used in physical gatherings as a ``backchannel'' to facilitate the conversations among participants. Studies have been centered around identifying the characteristics of such collective activities in different event settings. It has remained largely unexplored though, how event participants seek information in those situations. On the other hand, studies that examine information seeking in social media have not addressed the information needs in a particular social context. This study takes the first initiative to characterize the information seeking and responding networks in a concrete context---academic conferences---as one example of physical gatherings. By studying over 190 thousand tweets posted by 66 academic communities over five years, we unveil the landscape of information-seeking activities and the associated social and temporal contexts during the conferences. We leverage crowdsourcing and machine learning techniques to identify distinct types of information-seeking tweets in academic communities. We show that the information needs can be differentiated by their posted time and content, as well as how they were responded to. Interestingly, users' tendencies of posting certain types of information needs can be inferred by prior tweeting activities and network positions. Moreover, our results suggest it is also possible to predict the potential respondents to different types of information needs. Our study has implications for understanding the design of social search engines that facilitate the information seeking and responding in physical gatherings.