University of Kwazulu-Natal

Why People Share Misinformation On Social Media An Nature

Bonisiwe Shabane
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why people share misinformation on social media an nature

Humanities and Social Sciences Communications volume 12, Article number: 1129 (2025) Cite this article The widespread dissemination of misinformation on social media calls for an empirical investigation of why people share such content. By integrating affordance theory and flow theory, this study examines the underlying psychological mechanisms between social media affordances and misinformation sharing. With 533 valid questionnaires, the findings demonstrate that social media affordances (information accessibility, metavoicing and association) are positively associated with cognitive involvement and affective involvement, which then exert positive effects on users’ misinformation sharing. The results further reveal that emotional ability negatively moderates the relationship between affective involvement and misinformation sharing. Theoretically, our empirical findings extend prior studies by complementing the positive connotation of social media affordances and demonstrating that social media affordances can drive misinformation sharing through the mechanism of flow.

Practically, the findings imply that attention should be paid to the design and management of social media to curtail misinformation sharing. Misinformation has rapidly emerged on social media since the outbreak of the COVID-19 pandemic (Bermes, 2021; Chen and Fu, 2022). As social media have been increasingly embraced as an effective avenue for obtaining pandemic-related information, the problem of misinformation has exponentially grown on these platforms (Moravec et al. 2022). For example, Facebook has reportedly processed about 40,000 pieces of misinformation every day since the start of the pandemic (Gilmore, 2021). Owing to the widespread dissemination of misinformation and its potentially damaging effects, measures have been taken to check misinformation (Islam et al.

2020; Moravec et al. 2022). However, fact-checking lags behind the diffusion of misinformation and requires additional resources, which limits its effectiveness in curbing misinformation. Given the pervasiveness of misinformation on social media, it is pressing to understand what entices users to share misinformation on social media. Previous research largely regards misinformation sharing as a consequence of social media usage motivation (e.g., Apuke and Omar, 2021; Islam et al. 2020), information attributes (e.g., Zhou et al.

2021), social contexts (e.g., Kim and Dennis, 2019) or technical contexts (e.g., Bermes, 2021; Talwar et al. 2019). Although studies have confirmed that social media may amplify the issue of misinformation (Apuke and Omar, 2021; Kim and Dennis, 2019; Moravec et al. 2019), most existing studies regard social media as the background rather than the focal artifact of investigation, failing to fully profile the features of social media that contribute to misinformation sharing. By considering the role of social media in shaping users’ behavior, this study seeks to understand the role of social media in engendering misinformation sharing. The affordance lens of social media concerns what individuals can do by virtue of social media features (Lin and Kishore, 2021).

As behavior on social media hinges on its features and how users act on these features, the perspective of affordance is appropriate for understanding users’ misinformation sharing. Social media affordances have contradictory effects, and both positive and negative consequences can be activated (Majchrzak et al. 2013). Prior studies have emphasized desirable outcomes of social media affordances (Lin and Kishore 2021; Sun et al. 2020), ignoring unintended outcomes. To fill this gap, this study regards misinformation sharing as an undesirable outcome of social media affordances and proposes the first research question: how do social media affordances influence users’ misinformation sharing?

The researchers sought to understand how the reward structure of social media sites drives users to develop habits of posting misinformation on social media. (Photo/AdobeStock) The USC-led study of more than 2,400 Facebook users suggests that platforms — more than individual users — have a larger role to play in stopping the spread of misinformation online. USC researchers may have found the biggest influencer in the spread of fake news: social platforms’ structure of rewarding users for habitually sharing information. The team’s findings, published Monday by Proceedings of the National Academy of Sciences, upend popular misconceptions that misinformation spreads because users lack the critical thinking skills necessary for discerning truth from falsehood or because... Just 15% of the most habitual news sharers in the research were responsible for spreading about 30% to 40% of the fake news.

Received 2022 Oct 20; Revised 2023 Jan 7; Accepted 2023 Jan 12; Issue date 2023. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. Online social networks (OSNs) are rapidly growing and have become a huge source of all kinds of global and local news for millions of users. However, OSNs are a double-edged sword. Although the great advantages they offer such as unlimited easy communication and instant news and information, they can also have many disadvantages and issues.

One of their major challenging issues is the spread of fake news. Fake news identification is still a complex unresolved issue. Furthermore, fake news detection on OSNs presents unique characteristics and challenges that make finding a solution anything but trivial. On the other hand, artificial intelligence (AI) approaches are still incapable of overcoming this challenging problem. To make matters worse, AI techniques such as machine learning and deep learning are leveraged to deceive people by creating and disseminating fake content. Consequently, automatic fake news detection remains a huge challenge, primarily because the content is designed in a way to closely resemble the truth, and it is often hard to determine its veracity by AI...

This work aims to provide a comprehensive and systematic review of fake news research as well as a fundamental review of existing approaches used to detect and prevent fake news from spreading via OSNs. We present the research problem and the existing challenges, discuss the state of the art in existing approaches for fake news detection, and point out the future research directions in tackling the challenges. Keywords: Fake news, Disinformation, Misinformation, Information disorder, Online deception, Online social networks Fake news, disinformation and misinformation have become such a scourge that Marcia McNutt, president of the National Academy of Sciences of the United States, is quoted to have said (making an implicit reference to... Indeed, although online social networks (OSNs), also called social media, have improved the ease with which real-time information is broadcast; its popularity and its massive use have expanded the spread of fake news by... Fake news may refer to the manipulation of information that can be carried out through the production of false information, or the distortion of true information.

However, that does not mean that this problem is only created with social media. A long time ago, there were rumors in the traditional media that Elvis was not dead,2 that the Earth was flat,3 that aliens had invaded us,4, etc. Public Education Forum a NAFO Initiative Imagine this: you’re scrolling through your social media feed, and a shocking post grabs your attention. You feel compelled to share it. But did you pause to verify the information?

Many don’t—and new research reveals why certain people are more likely to spread false or misleading content. It’s not just about being careless or uninformed. The study, led by Ana Guinote and colleagues, finds that the motivation for power—wanting to influence and control others—plays a significant role in why people share information online, particularly misinformation. People driven by a desire for power often act as “brokers” of information, reshaping narratives and amplifying their reach. This isn’t limited to political elites or influencers; even everyday social media users with strong power motives can disproportionately shape online discussions. Social media platforms are designed to reward engagement, often amplifying polarizing or sensational content.

For power-motivated users, this creates an ideal environment to assert dominance and grow their networks. By sharing viral posts—whether true or not—they gain followers and become central figures in online communities.

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Humanities And Social Sciences Communications Volume 12, Article Number: 1129

Humanities and Social Sciences Communications volume 12, Article number: 1129 (2025) Cite this article The widespread dissemination of misinformation on social media calls for an empirical investigation of why people share such content. By integrating affordance theory and flow theory, this study examines the underlying psychological mechanisms between social media affordances and misinformation s...

Practically, The Findings Imply That Attention Should Be Paid To

Practically, the findings imply that attention should be paid to the design and management of social media to curtail misinformation sharing. Misinformation has rapidly emerged on social media since the outbreak of the COVID-19 pandemic (Bermes, 2021; Chen and Fu, 2022). As social media have been increasingly embraced as an effective avenue for obtaining pandemic-related information, the problem o...

2020; Moravec Et Al. 2022). However, Fact-checking Lags Behind The

2020; Moravec et al. 2022). However, fact-checking lags behind the diffusion of misinformation and requires additional resources, which limits its effectiveness in curbing misinformation. Given the pervasiveness of misinformation on social media, it is pressing to understand what entices users to share misinformation on social media. Previous research largely regards misinformation sharing as a co...

2021), Social Contexts (e.g., Kim And Dennis, 2019) Or Technical

2021), social contexts (e.g., Kim and Dennis, 2019) or technical contexts (e.g., Bermes, 2021; Talwar et al. 2019). Although studies have confirmed that social media may amplify the issue of misinformation (Apuke and Omar, 2021; Kim and Dennis, 2019; Moravec et al. 2019), most existing studies regard social media as the background rather than the focal artifact of investigation, failing to fully p...

As Behavior On Social Media Hinges On Its Features And

As behavior on social media hinges on its features and how users act on these features, the perspective of affordance is appropriate for understanding users’ misinformation sharing. Social media affordances have contradictory effects, and both positive and negative consequences can be activated (Majchrzak et al. 2013). Prior studies have emphasized desirable outcomes of social media affordances (L...