Shifting Attention: Modeling Follower Relationship Dynamics among US Emergency Management-related Organizations During a Colorado Wildfire
Published in Social Network Analysis of Disaster Response, Recovery, and Adaptation, 2016
Abstract
Emergency management organizations rarely act in a vacuum – both governmental and non-governmental organizations look to one another for topical information and practical guidance in both routine and non-routine settings. Although such attentional relationships have been historically difficult to study, the expansion of organizational activities into the online domain provides an opportunity to directly measure who is attending to whom in some settings. One such setting is Twitter, a popular microblogging service with a large emergency management presence. Here, we employ a Dynamic Network Logistic Regression (DNR) modeling approach to uncover the mechanisms that govern the evolving follower (i.e., subscription) relationships among a set of United States emergency management-related organizations (federal and state level) over an extended period during a Colorado wildfire. We relate features of the organizations’ temporally evolving structural position within this social network to their public information exchange patterns demonstrating a fairly complex pattern of historical dependence in attentional ties.
Recommended citation: Almquist, Z. W., Spiro, E. S., & Butts, C. T. (2017). Shifting attention: Modeling follower relationship dynamics among us emergency management-related organizations during a colorado wildfire. In Social network analysis of disaster response, recovery, and adaptation (pp. 93-112). Butterworth-Heinemann.
Download Paper