查看文章

The goal of this study is to examine how tweets containing distinct emotions (i.e., emotional tweets) and different information types (i.e., misinformation, corrective information, and others) are prevalent during the initial phase of mass shootings and furthermore, how users engage in those tweets.

The researchers manually coded 1,478 tweets posted between August 3–11, 2019, in the immediate aftermath of the El Paso and Dayton mass shootings. This manual coding approach systematically examined the distinct emotions and information types of each tweet.

The authors found that, on Twitter, misinformation was more prevalent than correction during crises and a large portion of misinformation had negative emotions (i.e., anger, sadness, and anxiety), while correction featured anger. Notably, sadness-exhibiting tweets were more likely to be retweeted and liked by …