Cargando…
Fake news and COVID-19: modelling the predictors of fake news sharing among social media users
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 phen...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7390799/ https://www.ncbi.nlm.nih.gov/pubmed/34887612 http://dx.doi.org/10.1016/j.tele.2020.101475 |
_version_ | 1783564516406067200 |
---|---|
author | Apuke, Oberiri Destiny Omar, Bahiyah |
author_facet | Apuke, Oberiri Destiny Omar, Bahiyah |
author_sort | Apuke, Oberiri Destiny |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7390799 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73907992020-07-30 Fake news and COVID-19: modelling the predictors of fake news sharing among social media users Apuke, Oberiri Destiny Omar, Bahiyah Telematics and Informatics Article 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. Elsevier Ltd. 2021-01 2020-07-30 /pmc/articles/PMC7390799/ /pubmed/34887612 http://dx.doi.org/10.1016/j.tele.2020.101475 Text en © 2020 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Apuke, Oberiri Destiny Omar, Bahiyah Fake news and COVID-19: modelling the predictors of fake news sharing among social media users |
title | Fake news and COVID-19: modelling the predictors of fake news sharing among social media users |
title_full | Fake news and COVID-19: modelling the predictors of fake news sharing among social media users |
title_fullStr | Fake news and COVID-19: modelling the predictors of fake news sharing among social media users |
title_full_unstemmed | Fake news and COVID-19: modelling the predictors of fake news sharing among social media users |
title_short | Fake news and COVID-19: modelling the predictors of fake news sharing among social media users |
title_sort | fake news and covid-19: modelling the predictors of fake news sharing among social media users |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7390799/ https://www.ncbi.nlm.nih.gov/pubmed/34887612 http://dx.doi.org/10.1016/j.tele.2020.101475 |
work_keys_str_mv | AT apukeoberiridestiny fakenewsandcovid19modellingthepredictorsoffakenewssharingamongsocialmediausers AT omarbahiyah fakenewsandcovid19modellingthepredictorsoffakenewssharingamongsocialmediausers |