Examining Public Perceptions of UK Rail Strikes: A Text Analytics Approach Using Twitter Data

Social media, particularly Twitter, has emerged as a vital platform for understanding public opinion on contemporary issues. This study investigates public attitudes towards UK rail strikes by analyzing Twitter data and provides a framework to assist policymakers in the RMT Union and the government in managing social media information. A dataset comprising tweets related to rail strikes from 25 June 2022 to 7 October 2022 was collected and multidimensional scaling and sentiment analysis techniques were employed to examine public opinions and sentiments. The analysis revealed that the predominant trends in tweets were dissatisfaction and negativity, with users expressing inconvenience caused by the rail strikes. Interestingly, the public also questioned the government's capabilities, with some suggesting that rail strikes were politically motivated events orchestrated by the government. Sentiment analysis results indicated that approximately 85% of tweets displayed negative sentiment towards the rail strikes. This research contributes to the understanding of public attitudes derived from tweet mining and offers valuable insights for academics and policymakers in interpreting public reactions to current events. Based on the findings, recommendations for the RMT Union are proposed through the lenses of stakeholder orientation theory and signaling theory. For instance, fostering public engagement can help reduce information asymmetry between the RMT Union and the public, enabling the union to better comprehend public sentiment towards rail strikes. The approach amalgamates these two theories, presenting a novel theoretical perspective for such investigations and extending their applicability, while also providing clear and in-depth recommendations for the RMT Union.