假新闻与新冠疫情:社交媒体用户间假新闻分享预测因素的建模分析

Fake news and COVID-19: modelling the predictors of fake news sharing among social media users.

作者信息

Apuke Oberiri Destiny, Omar Bahiyah

机构信息

School of Communication, Universiti Sains Malaysia, 11800 USM, Pulau Pinang, Malaysia.

Department of Mass Communication, Taraba State University, PMB 1167, Jalingo, Nigeria.

出版信息

Telemat Inform. 2021 Jan;56:101475. doi: 10.1016/j.tele.2020.101475. Epub 2020 Jul 30.

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 ( = 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 "" 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 was the most significant factor that predicted fake news sharing of COVID-19. We also found that social media users' motivations for and predicted the sharing of false information about COVID-19. In contrast, no significant association was found for motivation. We concluded with some theoretical and practical implications.

摘要

近几个月来,关于新冠疫情的假新闻传播有所增加,而导致此类错误信息分享的因素尚未得到充分研究。因此,本文描述了一项针对尼日利亚样本(n = 385)的关于新冠疫情假新闻传播情况的研究结果。假新闻现象采用使用与满足框架进行研究,并通过一个“……”动机进行了扩展。使用偏最小二乘法(PLS)对数据进行分析,以确定六个变量对假新闻分享结果的影响。我们的结果表明,……是预测新冠疫情假新闻分享的最显著因素。我们还发现,社交媒体用户的……和……动机预测了关于新冠疫情的虚假信息分享。相比之下,未发现……动机存在显著关联。我们得出了一些理论和实践意义。 (注:原文中存在部分未明确表述的内容,用“……”代替)

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