Antecedents of support for social media content moderation and platform regulation: the role of presumed effects on self and others

ABSTRACT

This study examines support for regulation of and by platforms and provides insights into public perceptions of platform governance. While much of the public discourse surrounding platforms evolves at a policy level between think tanks, journalists, academics and political actors, little attention is paid to how people think about regulation of and by platforms. Through a representative survey study of US internet users (N = 1,022), we explore antecedents of support for social media content moderation by platforms, as well as for regulation of social media platforms by the government. We connect these findings to presumed effects on self (PME1) and others (PME3), concepts that lie at the core of third-person effect (TPE) and influence of presumed influence (IPI) scholarship. We identify third-person perceptions for social media content: Perceived negative effects are stronger for others than for oneself. A first-person perception operates on the platform level: The beneficial effects of social media platforms are perceived to be stronger for the self than for society. At the behavioral level, we identify age, education, opposition to censorship, and perceived negative effects of social media content on others (PME3) as significant predictors of support for content moderation. Concerning support for regulation of platforms by the government, we find significant effects of opposition to censorship, perceived intentional censorship, frequency of social media use, and trust in platforms. We argue that stakeholders involved in platform governance must take more seriously the attitudes of their constituents.

KEYWORDS:

• Content moderation
• social media
• platform regulation
• third-person effect
• survey
• free speech

Acknowledgements

This paper is a project of the Digital Media Research Program at the University of Texas at Austin. It received partial funding from the Center for Media Engagement at the Moody College of Communication, University of Texas at Austin, as well as from the university’s Graduate School. The authors thank DMRP director Tom Johnson for his support, Alex Curry for his insight on data cleaning protocols and procedures, and Jay Jennings for his feedback on an earlier draft version. A version of this manuscript was first presented at the International Communication Association’s 2020 annual meeting, where it received a top student paper award from the Communication Law and Policy division.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 A relatively high rate of screen-outs can be explained by both our conservative quality criteria to protect the integrity of the collected dataset, as well as the length of the survey. Beyond what is reported, the survey also included dimensions on fake news, representation, (social) media and journalism. We carefully designed and pretested the questionnaire to avoid potential response bias. Few to no topically similar questions were asked prior to the ones used in this study, with the intent to avoid question order effects.

2 While we limited our analytical inquiry to PME3, PME1, and the effect of their summative term as suggested by the diamond method, we also calculated TPPs and entered them into the regression model. Neither in the content moderation nor the platform regulation model did TPP have a significant effect on the behavioral variables of support for regulation.

Additional information

Funding

This work was supported by The Graduate School, as well as by the Center for Media Engagement, both at the University of Texas at Austin.

Notes on contributors

Martin J. Riedl

Martin J. Riedl (MA, Hanover University of Music, Drama and Media; MA, Humboldt University of Berlin, Germany) is a doctoral candidate in the School of Journalism and Media, as well as a research associate for the Center for Media Engagement (CME) and for the Technology and Information Policy Institute (TIPI), all at The University of Texas at Austin, USA. His research interests include digital journalism, content moderation, media sociology, internet governance, and social media. His research has been published in Computers in Human Behavior, Digital Journalism, and Social Media + Society, among other journals [email: [email protected]].

Kelsey N. Whipple

Kelsey N. Whipple (PhD, The University of Texas at Austin) is an assistant professor at the University of Massachusetts-Amherst’s Journalism Department. Her research focuses on gender, gender identity and class in the media and the influence of social media and other technologies on journalism. Whipple’s work has been published in Journalism & Mass Communication Quarterly, Feminist Media Studies, and the Howard Journal of Communications, among other publications [email: [email protected]].

Ryan Wallace

Ryan Wallace (MS, California State University, San Marcos) is a doctoral candidate in the School of Journalism and Media at The University of Texas at Austin, USA. With an interdisciplinary background spanning the life, physical, and social sciences, his research interests center around mediated science communications with a particular focus on key issues such as: the Anthropocene, scientific misinformation, new media, and development in Latin America. His research has been published in #ISOJ: The Journal of the International Symposium on Online Journalism, as well as other texts [email: [email protected]].