RESEARCH ARTICLE Understanding the Uncertainty of Disaster Tweets and Its Effect on Retweeting: The Perspectives of Uncertainty Reduction Theory and Information Entropy Jaebong Son 1 | Jintae Lee 2 | Kai R. Larsen 2 | Jiyoung Woo 3 1 College of Business, California State University, Chico, California 2 Leeds School of Business, University of Colorado Boulder, Boulder, Colorado 3 Department of Big Data Engineering, Soonchunhyang University, Asan, Chungcheongnam-do, South Korea Correspondence Jaebong Son, College of Business, California State University, Chico, CA. Email: json@csuchico.edu Abstract The rapid and wide dissemination of up-to-date, localized information is a central issue during disasters. Being attributed to the original 140-character length, Twitter provides its users with quick-posting and easy-forwarding fea- tures that facilitate the timely dissemination of warnings and alerts. However, a concern arises with respect to the terseness of tweets that restricts the amount of information conveyed in a tweet and thus increases a tweetʼs uncer- tainty. We tackle such concerns by proposing entropy as a measure for a tweetʼs uncertainty. Based on the perspectives of Uncertainty Reduction The- ory (URT), we theorize that the more uncertain information of a disaster tweet, the higher the entropy, which will lead to a lower retweet count. By leveraging the statistical and predictive analyses, we provide evidence supporting that entropy validly and reliably assesses the uncertainty of a tweet. This study contributes to improving our understanding of information propa- gation on Twitter during disasters. Academically, we offer a new variable of entropy to measure a tweetʼs uncertainty, an important factor influencing disaster tweetsʼ retweeting. Entropy plays a critical role to better comprehend URLs and emoticons as a means to convey information. Practically, this research suggests a set of guidelines for effectively crafting disaster messages on Twitter. 1 | INTRODUCTION Disasters are inherently associated with lack of information due to the nature of dynamic, nonroutine events (Sellnow & Seeger, 2013). The affected public is motivated to seek disaster-related information to be aware of their sur- roundings (Boyle et al., 2004). While mainstream media play key roles in providing disaster information, it often lacks specific and timely information for people in the affected areas (Oh, Agrawal, & Rao, 2013). Social media, on the other hand, is known to convey localized and timely first-hand observations to inhabitants (Lachlan, Spence, Lin, & Del Greco, 2014). In particular, Twitter has received great attention from emergency practitioners, online volunteers, and academic scholars because of its communication characteristics: (i) improvised follower– followee 1 networks (Sutton et al., 2015) and (ii) short- length messages (or tweets) (Ma, Sun, & Cong, 2013). These characteristics allow Twitter users (or twitterers) to quickly post their tweets; instantly receive othersʼ tweets; and easily repost (or retweet) received tweets (Suh, Lichan, Pirolli, & Chi, 2010). Quick posting and easy reposting make Twitter one of the most effective mediums for disaster communication (Bean et al., 2016). For example, the original 140-alphanumeric character limit was beneficial for quickly updating situational Received: 17 February 2019 Revised: 29 October 2019 Accepted: 20 November 2019 DOI: 10.1002/asi.24329 Journal of the Association for Information Science and Technology. 2019;1–17. wileyonlinelibrary.com/journal/asi © 2019 ASIS&T 1