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Can Twitter messaging help corporations mitigate the impact of ethical scandals? We topic-model pre-scandal tweets of 92 ‘offenders’ to investigate

Can Twitter messaging help corporations mitigate the impact of ethical scandals? We topic-model... 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Society and Business Review Emerald Publishing

Can Twitter messaging help corporations mitigate the impact of ethical scandals? We topic-model pre-scandal tweets of 92 ‘offenders’ to investigate

Raheja, Shivani; Chipulu, Max
Society and Business Review , Volume 16 (3): 22 – Aug 2, 2021
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Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
1746-5680
eISSN
1746-5680
DOI
10.1108/sbr-10-2020-0122
Publisher site
See Article on Publisher Site

Abstract

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.

Journal

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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