Characterizing the role of influencers in disseminating situational information after an earthquake

Abstract

Influencers on social media play a crucial role in sharing situational information in disasters. Influencers have been defined in the literature as those with many followers/followees, many likes, actively involved in sharing information, and/or verified by social media platforms. This study collected Yiliang earthquake (Sichuan, China, 2012) data in Weibo and identified five types of situational information using supervised learning and text mining techniques. We found that influencers show (a) significant differences in the timing of sharing situational information; (b) significant positive effects on the propagation scale of all types of situational information, especially for casualties and damages, donations, and criticizing information; and (c) significant positive effects on the propagation speed of casualty and damage information and caution and advice information but significant negative effects on the propagation speed of help-seeking information. These findings have practical implications for authorities and researchers to understand the different roles of influencers in sharing situational information dissemination and designing appropriate influencer-specific information release strategies during a natural disaster.