Impact of Negative Emotions on X and Organizational Reputation Crisis: A Case Study of ArriveCan APP

Abstract

This study examines the reputational crisis created by the ArriveCan app, illustrating how negative platform X emotions configure crisis discourse in terms of emotional discourse, diffusion, and political commentary. Using the Integrated Crisis Mapping (ICM) scheme and Situational Crisis Communication Theory (SCCT), this study explores anger, frustration, anxiety, a sense of urgency, and distrust as prevalent emotional responses. Data were downloaded using a customized Python crawler and interpreted by ATLAS.ti, covering all 452 tweets in terms of emotional category, diffusion path, linguistic characteristics and political orientation. Emotions are shown not only to announce a loss of public trust but as agencies of agenda-setting and collective action as well. This paper argues that emotional expression is not on the margins but central in configuring reputational effects and public blame attribution.