Pass It On?: Retweeting in Mass Emergency

TLDR

Microblogging has rapidly become a widely adopted platform for emergency response, yet its diffuse, multi‑party information exchange practices are shaped by many forces and must be measured to guide future governance. This study examines microblogged content from two simultaneous natural hazard events in spring 2009 and focuses on how information propagates via Twitter’s retweet convention. The authors analyze retweet patterns and features of information redistribution within the Twitterverse to characterize propagation properties. They find that during emergencies, retweets from local users and tweets containing emergency terms are more likely to discuss the event, that users preferentially retweet content from local media and service organizations, and that local users redistribute information differently than the broader audience.

Abstract

We examine microblogged information generated during two different co-occurring natural hazards events in Spring 2009. Due to its rapid and widespread adoption, microblogging in emergency response is a place for serious consideration and experimentation for future application. Because microblogging is comprised of a set of practices shaped by a number of forces, it is important to measure and describe the diffuse, multi-party information exchange behaviors to anticipate how emergency governance might best play a role. Here we direct consideration toward information propagation properties in the Twitterverse, describing features of information redistribution related to the retweet (RT @) convention. Our analysis shows that during an emergency, for tweets authored by local users and tweets that contain emergency-related search terms, retweets are more likely than non-retweets to be about the event. We note that users are more likely to retweet information originally distributed through Twitter accounts run by media, especially the local media, and traditional service organizations. Comparing local users to the broader audience, we also find that tweet-based information redistribution is different for those who are local to an emergency event.