Fake news and COVID-19: modelling the predictors of fake news sharing among social media users
Publication type: Journal Article
Publication date: 2021-01-01
scimago Q1
wos Q1
SJR: 2.131
CiteScore: 20.4
Impact factor: 8.3
ISSN: 07365853, 1879324X
PubMed ID:
34887612
Electrical and Electronic Engineering
Computer Networks and Communications
Abstract
Fake news dissemination on COVID-19 has increased in recent months, and the factors that lead to the sharing of this misinformation is less well studied. Therefore, this paper describes the result of a Nigerian sample (n = 385) regarding the proliferation of fake news on COVID-19. The fake news phenomenon was studied using the Uses and Gratification framework, which was extended by an "altruism" motivation. The data were analysed with Partial Least Squares (PLS) to determine the effects of six variables on the outcome of fake news sharing. Our results showed that altruism was the most significant factor that predicted fake news sharing of COVID-19. We also found that social media users' motivations for information sharing, socialisation, information seeking and pass time predicted the sharing of false information about COVID-19. In contrast, no significant association was found for entertainment motivation. We concluded with some theoretical and practical implications.
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Total citations:
476
Citations from 2024:
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Apuke O. D. et al. Fake news and COVID-19: modelling the predictors of fake news sharing among social media users // Telematics and Informatics. 2021. Vol. 56. p. 101475.
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Apuke O. D., Omar B. Fake news and COVID-19: modelling the predictors of fake news sharing among social media users // Telematics and Informatics. 2021. Vol. 56. p. 101475.
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TY - JOUR
DO - 10.1016/j.tele.2020.101475
UR - https://doi.org/10.1016/j.tele.2020.101475
TI - Fake news and COVID-19: modelling the predictors of fake news sharing among social media users
T2 - Telematics and Informatics
AU - Apuke, Oberiri Destiny
AU - Omar, Bahiyah
PY - 2021
DA - 2021/01/01
PB - Elsevier
SP - 101475
VL - 56
PMID - 34887612
SN - 0736-5853
SN - 1879-324X
ER -
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@article{2021_Apuke,
author = {Oberiri Destiny Apuke and Bahiyah Omar},
title = {Fake news and COVID-19: modelling the predictors of fake news sharing among social media users},
journal = {Telematics and Informatics},
year = {2021},
volume = {56},
publisher = {Elsevier},
month = {jan},
url = {https://doi.org/10.1016/j.tele.2020.101475},
pages = {101475},
doi = {10.1016/j.tele.2020.101475}
}