User motivation in fake news sharing during the COVID-19 pandemic: an application of the uses and gratification theory

Apuke, Oberiri Destiny; Omar, Bahiyah

doi:10.1108/oir-03-2020-0116

Cited by 82 publications

(104 citation statements)

References 62 publications

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“…For example, Islam et al found that entertainment and self-promotion could promote the sharing of misinformation about COVID-19 [18]. Apuke and Omar found that altruism, instant news sharing, socialisation predicted fake news sharing related to the COVID-19 pandemic among social media users in Nigeria [19]. Laato et al suggested that a person's trust in online information and perceived information overload were strong predictors of unverified information sharing [6].…”

Section: Literature Reviewmentioning

confidence: 99%

Sharing of Verified Information about COVID-19 on Social Network Sites: A Social Exchange Theory Perspective

Xia

Zhou

2021

IJERPH

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Background: Verified and authentic information about coronavirus disease (COVID-19) on social networking sites (SNS) could help people make appropriate decisions to protect themselves. However, little is known about what factors influence people’s sharing of verified information about COVID-19. Thus, the purpose of this study was to explore the factors that influence people’s sharing of verified information about COVID-19 on social networking sites. Methods: Based on social exchange theory, we explore the factors that influence sharing of verified information about COVID-19 from two perspectives: benefits and costs. We employed the survey method to validate our hypothesized relationships. By using our developed measurement instruments, we collected 347 valid responses from SNS users and utilized the partial least squares method to analyze the data. Results: Among the benefits of sharing verified information about COVID-19, enjoyment in helping (β = 0.357, p = 0.000), altruism (β = 0.133, p = 0.029) and reputation (β = 0.202, p = 0.000) were significantly associated with verified information sharing about COVID-19. Regarding the costs of sharing verified information about COVID-19, both verification cost (β = −0.078, p = 0.046) and executional cost (β = −0.126, p = 0.011) also significantly affect verified information sharing about COVID-19. All the proposed hypotheses were supported. Conclusions: By exploring factors from both benefits and costs perspectives, we could understand users’ intention to share verified information about COVID-19 comprehensively. This study not only contributes to the literature on information sharing, but also has implications concerning users’ behaviors on SNS.

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Section: Literature Reviewmentioning

confidence: 99%

Sharing of Verified Information about COVID-19 on Social Network Sites: A Social Exchange Theory Perspective

Xia

Zhou

2021

IJERPH

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“…The level of scientific knowledge of users during public health emergencies refers to the basic literacy of individuals on health information and their ability to generate health information spreading behaviors in health crisis situations ( Fu et al., 2017 ; Nutbeam, 2000 ; Wood, 2018 ). Various models have considered the role of users' level of scientific knowledge on their willingness and ability to share online rumors ( Apuke & Omar, 2020 ; Suri et al., 2016 ); some scientists believe that a lack of scientific knowledge is one of the internal driving factors for the spread of rumors online ( Huo & Chen, 2020 ). In general, the level of scientific knowledge will affect the user's perceived risk efficiency and thus affect the user's behavioral decisions regarding the spread of online rumors and rumor-refuting information.…”

Section: Discussionmentioning

confidence: 99%

A rumor reversal model of online health information during the Covid-19 epidemic

Wang

et al. 2021

Information Processing & Management

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The development of the Internet and social media has expanded the speed and scope of information dissemination, but not all widely disseminated information is true. Especially during the public health emergencies, the endogenous health information demand generated by the lack of scientific knowledge of health information among online users stimulates the dissemination of health information by mass media while providing opportunities for rumor mongers to publish and spread online rumors. Invalid scientific knowledge and rumors will have a serious negative impact and disrupt social order during epidemic outbreaks such as COVID-19. Therefore, it is extremely important to construct an effective online rumor reversal model. The purpose of this study is to build an online rumor reversal model to control the spread of online rumors and reduce their negative impact. From the perspective of internal and external factors, based on the SIR model, this study constructed a G-SCNDR online rumor reversal model by adopting scientific knowledge level theory and an external online rumor control strategy. In this study, the G-SCNDR model is simulated, and a sensitivity analysis of the important parameters of the model is performed. The reversal efficiency of the G-SCNDR model can be improved by properly adopting the isolation-conversion strategy as the external control approach to online rumors with improving the popularization rate of the level of users' scientific knowledge and accelerating the transformation efficiency of official nodes. This study can help provide a better understanding of the process of online rumor spreading and reversing, as well as offering ceritain guidance and countermeasures for online rumor control during public health emergencies.

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“…Due to different goals, individuals have different needs when obtaining information, so they selectively adopt the information they perceive to be useful [ 46 ]. The perceived usefulness of COVID-19 videos with different content is different, which is reflected in the difference in their popularity [ 27 ]. Therefore, the content type of the video is related to the perceived usefulness of the information.…”

Section: Theoretical Background and Hypothesismentioning

confidence: 99%

“…Popularity level can be used to express the results of information adoption. In the study of YouTube, popularity level was measured by views and the level of positive feedback (e.g., liking rate(likes/(likes + dislikes) × 100)) [ 25 , 27 , 63 ]. The measurement index of audience feedback is determined according to the ways that audiences can socialize on the platform.…”

Section: Theoretical Background and Hypothesismentioning

confidence: 99%

“…Several obvious gaps in the current study could be narrowed. First of all, studies on the transmission of text information have used a variety of different platforms as data sources, including Twitter [ 24 , 25 ], Weibo [ 26 ], and Facebook [ 27 ]. However, most research on epidemic information spread in the form of video has used the YouTube platform as the information source [ 28 , 29 , 30 , 31 ].…”

Section: Introductionmentioning

confidence: 99%

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Research on the Influencing Factors of Audience Popularity Level of COVID-19 Videos during the COVID-19 Pandemic

Liu

2021

Healthcare

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(1) Background: During the COVID-19 pandemic, users share and obtain COVID-19 information through video platforms, but only a few COVID-19 videos become popular among most audiences. Therefore, it is a very interesting and important research question to explore the influencing factors of the popularity of COVID-19 videos during the COVID-19 pandemic; (2) Our research collects video data related to the keyword “COVID-19” on video platform, the data are analyzed by content analysis and empirical analysis. We then constructed a theoretical model based on the information adoption model; (3) A total of 251 videos were divided into three categories. The least common category was the data and analysis category (11.2%), followed by the prevention and control status category (13.5%); the knowledge and general science category was the most common (75.3%). From the perspective of video quality, the information sources of most videos are relatively reliable, and the content of medical information is low. The research results showed that short video lengths, longer descriptions, more reliable video sources and lower medical information content were more popular with audiences. Audiences are more likely to be attracted to videos in the prevention and control status category and knowledge and general science category. Videos uploaded by uploaders who have a higher influence are more popular with audiences; (4) Conclusion: During the COVID-19 pandemic, information quality (video length, description length, video content type, and medical information and content index) and source credibility (information source reliability, influence and certification type) all significantly influence the popularity level of COVID-19 videos. Our research conclusions can provide management suggestions for the platform, make videos released by uploaders more popular with audiences, and help audiences better understand COVID-19 information and make prevention and control efforts.

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User motivation in fake news sharing during the COVID-19 pandemic: an application of the uses and gratification theory

Cited by 82 publications

References 62 publications

Sharing of Verified Information about COVID-19 on Social Network Sites: A Social Exchange Theory Perspective

Sharing of Verified Information about COVID-19 on Social Network Sites: A Social Exchange Theory Perspective

A rumor reversal model of online health information during the Covid-19 epidemic

Research on the Influencing Factors of Audience Popularity Level of COVID-19 Videos during the COVID-19 Pandemic

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