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

Author:

Raheja Shivani,Chipulu Max

Abstract

Purpose This paper aims to examine whether Twitter messaging can help mitigate the harm corporations suffer in the aftermath of ethical scandals. Design/methodology/approach This 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. Findings LDA 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 implications Provided 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/value The paper offers a first exploration of the relevance of corporate Twitter messaging in mitigating ethical scandals.

Publisher

Emerald

Subject

Organizational Behavior and Human Resource Management,Strategy and Management,Business, Management and Accounting (miscellaneous),Business and International Management

Reference75 articles.

1. Al, M., Breckon, T., Matthews, P. and McGough, A. (2016), “SMS spam filtering using probabilistic topic modelling and stacked denoising autoencoder”, Paper presented at the 25th International Conference on Artificial Neural Networks (ICANN 2016).

2. The measurement and antecedents of affective, continuance and normative commitment to the organization;Journal of Occupational Psychology,1990

3. How do the news media frame crises? A content analysis of crisis news coverage;Public Relations Review,2009

4. Communicating effectively about CSR on twitter;Internet Research,2018

5. Bachmann, R., Ehrlich, G. and Ruzic, D. (2017), “Firms and collective reputation: the Volkswagen emission scandal as a case study: CESifo working paper”.

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