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Cited by 431

The DOI matches its Crossref record; 89 of the 89 references it cites were found in a registry or an index.

Fake news, social media and marketing: A systematic review

Open access
Domenico, Giandomenico Di, Sit, Jason, Ishizaka, Alessio, Nunan, Daniel·2021·Journal of Business Research

Abstract

There is growing concern amongst policy makers, managers and academic researchers over the role that social media plays in spreading misinformation, widely described as ‘Fake News’. However, research to date has mainly focussed on the implications of fake news for political communication and debate. There has been less focus on the implications of social media misinformation upon marketing and consumers. Given the key role of social media as a communication platform, there is a gap in our understanding of fake news through a consumer lens. We address this gap by conducting an interdisciplinary systematic review of the relevant literature. Through critical evaluation and synthesis of the literature, we identify five themes that explain the fake news phenomenon: the dissemination process, spreading channel features, outcomes, fabricated legitimacy and attitudes. Finally, we propose a theoretical framework that highlights themes’ relationships and research propositions to guide future research in this area.

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Crossref · 10.1016/j.jbusres.2020.11.037

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Metadata

Authors
Domenico, G. D., Sit, J., Ishizaka, A., & Nunan, D.
Venue
Journal of Business Research
Publisher
Elsevier BV
Published
2021-01
Volume
124
Pages
329-341
ISSN
0148-2963 (ISSN-L)
OpenAlex
W3111430045
Cited by
431
References
89
FWCI
13.80
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Fake news, social media and marketing: A systematic review. https://app.cochat.ai/papers/10.1016/j.jbusres.2020.11.037
The paper
Domenico, G. D., Sit, J., Ishizaka, A., & Nunan, D. (2021). Fake news, social media and marketing: A systematic review. Journal of Business Research. https://doi.org/10.1016/j.jbusres.2020.11.037

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.