The established link between trauma-related media exposure and distress may be cyclical: Distress can increase subsequent trauma-related media consumption that promotes increased distress to later events. We tested this hypothesis in a 3-year longitudinal study following the 2013 Boston Marathon bombings and the 2016 Orlando Pulse nightclub massacre using a national U.S. sample (N= 4165). Data were collected shortly after the bombings, 6 and 24 months post-bombings, and beginning 5 days after the Pulse nightclub massacre (approximately 1 year later; 36 months post-bombings). Bombing-related media exposure predicted posttraumatic stress symptoms (PTS) 6 months later; PTS predicted worry about future negative events 2 years after the bombings, which predicted increased media consumption and acute stress following the Pulse nightclub massacre 1 year later. Trauma-related media exposure perpetuates a cycle of high distress and media use.

SignificanceDuring active shooter events when danger is imminent and official information is disseminated inconsistently, ambiguity is high. In these situations, individuals may seek information from unofficial channels (e.g., social media), thereby exposing themselves to unverified information and rumors. In a study of students caught in a university-wide lockdown, we found that those who relied on social media for updates reported increased exposure to conflicting information. Moreover, those who trusted what they read reported greater distress. Then, using a big-data analysis of Twitter data spanning ∼5 hours surrounding the event, we demonstrated that rumor transmission tracks with community-level negative emotion during gaps in official communication. Officials should monitor social media channels to mitigate the negative impact of rumors during collective traumas.

Studying communities impacted by traumatic events is often costly, requires swift action to enter the field when disaster strikes, and may be invasive for some traumatized respondents. Typically, individuals are studied after the traumatic event with no baseline data against which to compare their postdisaster responses. Given these challenges, we used longitudinal Twitter data across 3 case studies to examine the impact of violence near or on college campuses in the communities of Isla Vista, CA, Flagstaff, AZ, and Roseburg, OR, compared with control communities, between 2014 and 2015. To identify users likely to live in each community, we sought Twitter accounts local to those communities and downloaded tweets of their respective followers. Tweets were then coded for the presence of event-related negative emotion words using a computerized text analysis method (Linguistic Inquiry and Word Count, LIWC). In Case Study 1, we observed an increase in postevent negative emotion expression among sampled followers after mass violence, and show how patterns of response appear differently based on the timeframe under scrutiny. In Case Study 2, we replicate the pattern of results among users in the control group from Case Study 1 after a campus shooting in that community killed 1 student. In Case Study 3, we replicate this pattern in another group of Twitter users likely to live in a community affected by a mass shooting. We discuss conducting trauma-related research using Twitter data and provide guidance to researchers interested in using Twitter to answer their own research questions in this domain. (PsycINFO Database Record

Traditional and new media inform and expose the public to potentially distressing graphic content following disasters, but predictors of media use have received limited attention. We