Individual’s behavior and sentiment in online environments have become increasingly reactive to disaster events. Monitoring and analyzing these behaviors and sentiments in the context of manmade disasters provides valuable insights for crisis management professionals. These analytical processes help develop a comprehensive understanding of evolving situations, support effective response strategies, and contribute to societal stability. Employing appropriate methodologies and tools enables the capture and tracking of semantic shifts in social media communications, offering a means to observe their evolution over time.
In this study, we present research conducted on the Manchester Arena Bombing incident in the United Kingdom, which occurred on May 22, 2017, focusing on leveraging data from Twitter (now X). Using Orange, a text-mining analysis software, we explored key discussion topics and their dynamics from messages published immediately after the incident up to a week and a month later. The results demonstrate the evolution of emotional expressions in citizens’ messages during each disaster phase analyzed, including the prevalence of negative and positive sentiments during the recovery phase.