Please submit paper abstracts to the Sunbelt 2019 session on Computational Social Science and Social Network Theory. Due by Friday January 31, 2020.
Organizer: James A. Kitts (Computational Social Science Institute, Sociology, University of Massachusetts)
Session Description: Empirical lenses emerging from the field of computational social science – wearable sensors, location-aware devices, electronic calendar meetings, logs of phone calls, messages, online transactions, etc. – produce streaming histories of events that have supported an explosion of large scale empirical social network analysis. Most such analyses aggregate interactions, turning time-stamped events into temporally continuous ties. For example, more than five messages exchanged between actors in a month may be coded as a dyadic tie for that entire month. The result may be interpreted as a temporally continuous (and concurrent) network that applies to conventional social network theories such as network exchange theory or structural balance theory. Some recent work has moved beyond this temporal aggregation to directly analyze structural-temporal dependencies in interaction events. This session will consider the interface of social network theory and computational social science data, emphasizing two kinds of contributions: 1) Theoretical or conceptual papers that aim to help us develop or adapt social network theories to the context of streaming interaction data; 2) Empirical papers that analyze dynamic patterns of interaction events and try to grapple with those patterns using explicit theories about underlying processes.
Use this link to submit your abstract before January 31, 2020.
James A. Kitts
Department of Sociology, Professor
Computational Social Science Institute, Core Faculty
University of Massachusetts
200 Hicks Way
Amherst, MA 01003-9277