This paper investigates the shared emotional responses of Twitter users in the aftermath of a massive data breach, a crisis event known as the Office of Personnel Management (OPM) data breach of 2015. This breach impacted the lives of several million individuals due to the exposure of sensitive and personally identifying information. We take a data exploration approach to analyzing over 18,000 tweet messages of the ensuing discussion that took place after public notification that the breach had occurred. The resulting analysis reveals that although the emotions of anxiety, anger, and sadness may initially appear erratic, at an aggregate level, the public display of these emotions corresponds to the situational awareness of the breach event. Further, our analysis finds that this relationship extends to the sharing of emotions, indicating those participating in the conversation congregate around a sense of shared emotional experience. Finally, an in-depth analysis of the ensuing dialogue identifies the most salient conversational drivers of these emotions, revealing breach concepts most significantly related to each emotion. Based on the results, we present propositions that draw from this analysis to inform emotional response characteristics that emerge over the duration of such crisis events. The results of this study can inform organizational practices and policy making in the context of response to crisis events such as data breaches.
The OPM Data Breach: An Investigation of Shared Emotional Reactions on Twitter
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SKU
46.2.06
Publication History
Received: June 20, 2018
Revised: June 10, 2019; October 15, 2020; April 5, 2021
Accepted: May 5, 2021
Published Online as Articles in Advance: May 24, 2022
Published Online in Issue: June 1, 2022
Abstract
Additional Details
Author | Eric Bachura, Rohit Valecha, Rui Chen, and H. Raghav Rao |
Year | 2022 |
Volume | 46 |
Issue | 2 |
Keywords | Data breach, emotional response, situation awareness, OPM hack, Twitter, data-driven research, crisis management, word-to-vector, W2V |
Page Numbers | 881-910; DOI: 10.25300/MISQ/2022/15596 |