Tracking and Analyzing Individual Distress Following Terrorist Attacks Using Social Media Streams

Abstract

Risk research has theorized a number of mechanisms that might trigger, prolong, or potentially alleviate individuals' distress following terrorist attacks. These mechanisms are difficult to examine in a single study, however, because the social conditions of terrorist attacks are difficult to simulate in laboratory experiments and appropriate preattack baselines are difficult to establish with surveys. To address this challenge, we propose the use of computational focus groups and a novel analysis framework to analyze a social media stream that archives user history and location. The approach uses time-stamped behavior to quantify an individual's preattack behavior after an attack has occurred, enabling the assessment of time-specific changes in the intensity and duration of an individual's distress, as well as the assessment of individual and social-level covariates. To exemplify the methodology, we collected over 18 million tweets from 15,509 users located in Paris on November 13, 2015, and measured the degree to which they expressed anxiety, anger, and sadness after the attacks. The analysis resulted in findings that would be difficult to observe through other methods, such as that news media exposure had competing, time-dependent effects on anxiety, and that gender dynamics are complicated by baseline behavior. Opportunities for integrating computational focus group analysis with traditional methods are discussed.

Neighborhood disadvantage, residents' distress, and online social communication: Harnessing Twitter data to examine neighborhood effects

“…Similarly, over the past 5 years, social media has been increasingly used to understand the psychological and behavioral outcomes of individuals in a range of settings such as disasters (Lin & Margolin, ; Lin, Margolin, & Wen, ). This line of research examines the linguistic features of individuals’ social media posts to derive inferences about their mental health outcomes, the findings of which have been consistent with the studies of linguistic expressions among individuals with mental illness in clinical settings (Oxman, Rosenberg, & Tucker, ; Rude, Gortner, & Pennebaker, ).…”

“…Similarly, over the past 5 years, social media has been increasingly used to understand the psychological and behavioral outcomes of individuals in a range of settings such as disasters (Lin & Margolin, 2014;Lin, Margolin, & Wen, 2017).…”

How a terror attack affects right‐wing authoritarianism, social dominance orientation, and their relationship to torture attitudes

“…One hundred fifty-two of them (95 women; 54 men; 3 did not report sex; Age M = 22.91; SD = 2.66) were in the terror salient condition, namely, the week immediately after the attacks. This was a time-period where public reactions to the attacks were characterized by high anxiety, anger and sadness (Lin, Margolin & Wen, 2017) and by expressions of sympathy such as "Today we are all Parisians" and the like. The general population was also exposed to intense reporting of the attack from the media (about 455 articles a day in the national news media).…”

Advances in Risk Analysis with Big Data

“…Discerning theoretically meaningful inferences from the cacophonous stream of social media conversation, particularly after a terrorist attack, is a challenge, however. In this special issue, Lin et al (26) propose an innovative research design and analysis framework to address the challenge. The approach identifies users whose social media usage indicates they were near to an attack at the time it occurred.…”