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Open Access

Optimizing the Service Efficacy of Crowd Ratings in Curbing Fake News Dissemination on Social Media

Qian Liu1, Yang Lyu2, Jian Tang3( ), Weiguo Fan4
China Center for Internet Economy Research, Central University of Finance and Economics, Beijing 100081, China
School of Population and Health, Renmin University of China, Beijing 100081, China
School of Information, Central University of Finance and Economics, Beijing 100081, China
Tippie College of Business, University of Iowa, Iowa City, IA 52242, USA
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Abstract

Curbing the dissemination of fake news in social media has been a major issue in recent years. Previous studies have suggested that the general public can recognize fake news, showing the feasibility of applying crowd ratings to identify fake news. However, the effectiveness of crowd ratings for curbing the dissemination of fake news is uncertain. This study constructed an online experimental platform to simulate Sina Microblog and designed a crowd rating strategy to compare and validate the difference between the absence vs. the presence of crowd ratings, and crowd ratings vs. expert ratings, in curbing the dissemination of fake news. We found that the presence of crowd ratings inhibited users’ dissemination of fake news compared to the absence of crowd ratings. Moreover, there was no significant difference between the suppression effects of crowd ratings and expert ratings, both of which were effective in curbing the dissemination of fake news. Crowd rating uses collective intelligence to intervene in users’ perceptions and behaviors at the onset of fake news dissemination, providing a cost-effective and efficient solution to combat the spread of fake news on social media.

Keywords

social mediafake news disseminationcrowd ratingexpert ratingcontainment strategies

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International Journal of Crowd Science
Volume 8 Issue 3,
September 2024
Pages 110-121
DOI: 10.26599/IJCS.2024.9100020
Cite this article:
Liu Q, Lyu Y, Tang J, et al. Optimizing the Service Efficacy of Crowd Ratings in Curbing Fake News Dissemination on Social Media. International Journal of Crowd Science, 2024, 8(3): 110-121. https://doi.org/10.26599/IJCS.2024.9100020

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Published: 19 August 2024
© The author(s) 2024.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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