University Community Members’ Perceptions of Labels for Online Media

Ryan Suttle, Scott Hogan, Rachel Aumaugher, Matthew Spradling, Zak Merrigan and Jeremy Straub
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Ryan Suttle: Department of Mathematics & Applied Sciences, University of Michigan-Flint, Flint, MI 48502, USA
Scott Hogan: Department of Mathematics & Applied Sciences, University of Michigan-Flint, Flint, MI 48502, USA
Rachel Aumaugher: Department of Mathematics & Applied Sciences, University of Michigan-Flint, Flint, MI 48502, USA
Matthew Spradling: Department of Mathematics & Applied Sciences, University of Michigan-Flint, Flint, MI 48502, USA
Zak Merrigan: Department of Computer Science, North Dakota State University, 3950 Campus Road, Stop 9015, Grand Forks, ND 58202, USA
Jeremy Straub: Department of Computer Science, North Dakota State University, 3950 Campus Road, Stop 9015, Grand Forks, ND 58202, USA

Future Internet, 2021, vol. 13, issue 11, 1-39

Abstract: Fake news is prevalent in society. A variety of methods have been used in an attempt to mitigate the spread of misinformation and fake news ranging from using machine learning to detect fake news to paying fact checkers to manually fact check media to ensure its accuracy. In this paper, three studies were conducted at two universities with different regional demographic characteristics to gain a better understanding of respondents’ perception of online media labeling techniques. The first study deals with what fields should appear on a media label. The second study looks into what types of informative labels respondents would use. The third focuses on blocking type labels. Participants’ perceptions, preferences, and results are analyzed by their demographic characteristics.

Keywords: fake news; media labeling; misinformation; perceptions of labeling online content; deliberately deceptive content (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2021
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