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Past, present and future impact of social media on health workers’ mental health: a text mining approach

Chowdhury Noushin Novera (Department of Business and Technology Management, Islamic University of Technology, Gazipur, Bangladesh)
Regina Connolly (DCU Business School, Dublin City University, Dublin, Ireland)
Peter Wanke (COPPEAD Graduate Business School, Federal University, Rio de Janeiro, Brazil)
Md. Azizur Rahman (Department of Business Administration, Daffodil International University, Dhaka, Bangladesh)
Md. Abul Kalam Azad (Department of Business and Technology Management, Islamic University of Technology, Gazipur, Bangladesh)

Journal of Modelling in Management

ISSN: 1746-5664

Article publication date: 17 January 2023

Issue publication date: 2 January 2024

801

Abstract

Purpose

The COVID-19 epidemic has brought attention to the variables that influence the mental health of health workers who are entrusted with nursing individuals. Despite the fact that many articles have examined the effects of social media usage on mental health, there is a lack of research synthesizing learning from this body of research. The purpose of this study is to use text mining and citation-based bibliometric analysis to conduct a detailed review of extant literature on health workers’ mental health and social networking habits.

Design/methodology/approach

This study conducts a full-text analysis of 36 articles selected on health workers' mental health and social media using text-mining techniques in R programming and a bibliometric citation analysis of 183 papers from the Scopus database in VOS viewer software. But the limitations of the methods used in this study are that the bibliometric analysis was limited to the Scopus database because the VOS viewer program did not support any other database and the text-mining approach caused the natural processing redundancy.

Findings

The bibliometric analysis reveals the thematic networks that exist in the literature of health workers’ mental health and social networking. The findings from text mining identified ten topic models, which helped to find the related papers classified in ten different groups and are provided alongside a summary of the published research and a list of the primary authors with posterior probability through Latent Dirichlet Allocation.

Originality/value

To the best of the authors’ knowledge, this is the first hybrid review, combining text mining and bibliometric review, on health workers’ mental health where social networking plays a moderating role. This paper critically provides an overview of the impact of social networking on health workers' mental health, presents the most important and frequent topics, introduces the scientific visualization of articles published in the Scopus database and suggests further research avenues. These findings are important for academics, health practitioners and medical specialists interested in learning how to better support the mental health of health workers using social media.

Keywords

Citation

Novera, C.N., Connolly, R., Wanke, P., Rahman, M.A. and Azad, M.A.K. (2024), "Past, present and future impact of social media on health workers’ mental health: a text mining approach", Journal of Modelling in Management, Vol. 19 No. 1, pp. 1-18. https://doi.org/10.1108/JM2-05-2022-0135

Publisher

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Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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