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This paper aims to examine whether Twitter messaging can help mitigate the harm corporations suffer in the aftermath of ethical scandals.Design/methodology/approachThis paper applies Web Application Programming Interfaces (API) on the Guardian and New York Times news archives to find corporations that suffered scandals between 2014 and 2019, revealing 92 publicly listed companies in the UK. Using Twitter API and the Python library, Getoldtweets, this paper extracts historical, pre-scandal – i.e. pre-2014 – tweets of the 92 firms. The paper topic-models the tweets data using Latent Dirichlet Allocation (LDA). This paper then subjects the topics to multidimensional scaling (MDS) to examine commonalities among them.FindingsLDA reveals 10 topics, which group under 5 themes; these are product marketing, urgent signalling of “greenness”, customer relationship management, corporate strategy and news feeds. MDS suggests that the topics further congregate into two meta-themes of future-oriented versus immediate and individual versus global.Practical implicationsProvided they are sincere and legitimate, corporations’ tweets on global issues with a green agenda should help cushion the impact of ethical scandals. Overall, however, the findings suggest that Twitter messaging could be a double-edged sword, and underscore the importance of strategy.Originality/valueThe paper offers a first exploration of the relevance of corporate Twitter messaging in mitigating ethical scandals.
Society and Business Review – Emerald Publishing
Published: Aug 2, 2021
Keywords: Multi-dimensional scaling; Topic modelling; Latent Dirichlet allocation; Ethical reputation; Ethical scandal; Twitter messaging
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