2024/04/11 by Chenyan Jia, Taeyoung Lee · 1 voice
Computer Science · Social Sciences · #Hate Speech and Cyberbullying Detection #Media Studies and Communication #Misinformation and Its Impacts
paper · doi:10.37016/mr-2020-138
openalex publication_date 2024/04/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
While algorithms and crowdsourcing have been increasingly used to debunk or label misinformation on social media, such tasks might be most effective when performed by professional fact checkers or journalists. Drawing on a national survey (N = 1,003), we found that U.S. adults evaluated fact-checking labels created by professional fact-checkers as more effective than labels by algorithms and other users. News media labels were perceived as more effective than user labels but not statistically different from labels by fact checkers and algorithms. There was no significant difference between labels created by users and algorithms. These findings have implications for platforms and fact-checking practitioners, underscoring the importance of journalistic professionalism in fact-checking.