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 features 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 uncertainty. We tackle such concerns by proposing entropy as a measure for a tweetʼs uncertainty. Based on the perspectives of Uncertainty Reduction Theory (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 propagation 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.

中文翻译：

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理解灾难推文的不确定性及其对转发的影响：不确定性降低理论和信息熵的视角

快速、广泛地传播最新的本地化信息是灾害期间的一个核心问题。由于最初的 140 个字符长度，Twitter 为其用户提供了快速发布和易于转发的功能，有助于及时发布警告和警报。然而，人们担心推文的简洁性限制了推文中传达的信息量，从而增加了推文的不确定性。我们通过提出熵作为推文不确定性的度量来解决这些问题。基于不确定性降低理论（URT）的观点，我们推测灾难推文的不确定信息越多，熵越高，这将导致转发次数越少。通过利用统计和预测分析，我们提供证据支持熵有效且可靠地评估推文的不确定性。这项研究有助于提高我们对灾难期间 Twitter 上信息传播的理解。在学术上，我们提供了一个新的熵变量来衡量推文的不确定性，这是影响灾难推文转发的重要因素。熵在更好地理解 URL 和表情符号作为传达信息的手段方面起着至关重要的作用。实际上，这项研究提出了一套指导方针，用于在 Twitter 上有效地制作灾难信息。影响灾难推文转发的重要因素。熵在更好地理解 URL 和表情符号作为传达信息的手段方面起着至关重要的作用。实际上，这项研究提出了一套指导方针，用于在 Twitter 上有效地制作灾难信息。影响灾难推文转发的重要因素。熵在更好地理解 URL 和表情符号作为传达信息的手段方面起着至关重要的作用。实际上，这项研究提出了一套指导方针，用于在 Twitter 上有效地制作灾难信息。