Loading...
ONLINE MISINFORMATION AND FACT-CHECKING
Shan, Guohou
Shan, Guohou
Citations
Altmetric:
Genre
Thesis/Dissertation
Date
2024-08
Advisor
Committee member
Group
Department
Business Administration/Management Information Systems
Subject
Permanent link to this record
Collections
Research Projects
Organizational Units
Journal Issue
DOI
http://dx.doi.org/10.34944/dspace/10601
Abstract
Social media platforms have begun to counter false news by integrating fact-checking services. These fact-checkers verify posts’ content and inform users about the posts’ veracity before engaging with them. While the efficacy of fact-checking on users has been studied in prior literature, little attention has been paid to the factors that determine the effectiveness of fact-checking (e.g., fact-checking timeliness, types of fact-checkers, and poster reputation) to sway user reactions. Hence, I design three essays aiming to understand the factors that affect the fact-checking effectiveness. The first essay examines the effectiveness of fact-checking by using a multi-method study. The multi-method study leverages the high external validity of observational data from Twitter (Study 1) complemented by the high internal validity of experimental data (Study 2) to build insights into how fact-checking methods and timeliness affect news engagement (i.e., willingness to read, like, comment, share, bookmark, and denounce). When fact-checkers flag news as false, we found it significantly decreases news engagement and that fact-checking timeliness moderates the effect of fact-checking. Moreover, we find that fact-checking affects news engagement by influencing users’ evaluation of the news believability and anticipation. Our findings enrich the understanding of the impact of fact-checking on users’ engagement with news and suggest managerial implications for reducing false news engagement. The second essay focuses on understanding how different types of fact-checkers may affect users’ news engagement differently. It explores how the different types of fact-checkers (i.e., AI or human) impact believability and engagement with news that is flagged as false. Building on source credibility theory, we evaluate how the reputation of the person posting the news and the political orientation of the user reading the news (i.e., progressive or conservative) moderate the impact of AI vs. human fact-checkers. We examine this interaction in two separate 3×2×2 online quasi-experiments conducted in the United States and the United Kingdom. In both studies, we found differences regarding the impact of fact-checker type and moderating impacts for poster reputation and user political orientation. Our results show that AI fact-checkers are more effective than human fact-checkers in reducing news believability and engagement among progressive users. We also found that a high news poster reputation can further enhance this impact. By investigating the interplay between the fact-checker type, the poster, and user political orientation and comparing results across two countries, we extend the understanding of the impact of different types of fact-checkers on news believability and user engagement with false news on social media platforms. Finally, we derive managerial implications for mitigating the spread of false news on social media platforms.
The third essay seeks to understand the determinants of the crowdsourced fact-checking. Crowdsourced fact-checking solutions have emerged as a promising means of detecting misinformation on social media. Because fact-checking often requires the evaluation of controversial or politicized social media posts, anonymity has been suggested as essential to persuade users to voluntarily fact-check news. This paper reports the results of a multi-method investigation of the mechanisms that shape how identity anonymity affects crowdsourced fact-checking contributions. In Study 1, we use observational data from Twitter and conduct a regression discontinuity design (RDD) to examine whether and when identity anonymity affects the quantity and quality of fact-checking. We find that identity anonymity does not affect the quantity of posts; instead, it increases the quality of fact-checking. Furthermore, we find that the impact of anonymity on quality is significantly higher for users with longer fact-checking tenure. In Study 2, we use online experiments to test the proposed mechanisms and find that perceived social presence, perceived self-efficacy, and perceived fact-checking responsibility help explain the effect of anonymity on users' fact-checking intentions. We also find that identity anonymity affects contributions differently across news categories. By unpacking these mechanisms, we offer insights for researchers and practitioners interested in understanding how identity anonymity changes the quality of fact-checking, and explain why crowdsourced users offer more or less reliable ratings of the veracity of social media posts.
Overall, this three-essay dissertation will enrich the understanding of the impacts of fact-checking, different types of fact-checkers, and the antecedents of crowdsourced fact-checking on social media.
Description
Citation
Citation to related work
Has part
ADA compliance
For Americans with Disabilities Act (ADA) accommodation, including help with reading this content, please contact scholarshare@temple.edu