Dynamics of Personal Responses to Terror Attacks: A Temporal Network Analysis Perspective

: In this paper, we analyze responses to terror attacks through the lens of the Terror Management Theory. We focus on the temporal evolution of Twitter messages that convey death anxiety, emotional pain, as well as positivity. We model the responses to terror attacks as personal reactions that include the use of a first person singular pronoun along with cues of affect and personal concerns. In order to detect these textual features, we used the Linguistic Inquiry and Word Count (LIWC) tool. Our data-set includes tweets related to three terror attacks: the 2017 Manchester terror attack, the 2019 Christchurch terror attack, and the 2020 Vienna terror attack. Our analysis is based on 3.8 million tweets that have been sent by 1.6 million users. The results indicate that positive messages associated with the use of religious words (e.g., messages of prayers and hope) dominate over those that convey emotional pain and fear of death. This points to a tendency to spread hope and empathy in the aftermath of a terror attack. We found that the acute phase of a terror attack exhibits a high volume of messages that sharply decline in the immediate aftermath. In contrast, positive messages exhibit smaller peaks even one week after a terror attack happened.