TY - JOUR
T1 - Analyzing Misinformation Claims During the 2022 Brazilian General Election on WhatsApp, Twitter, and Kwai
AU - Hale, Scott A.
AU - Belisario, Adriano
AU - Mostafa, Ahmed Nasser
AU - Camargo, Chico
N1 - Publisher Copyright:
© The Author(s) 2024.
PY - 2024
Y1 - 2024
N2 - This study analyzes misinformation claims sent to fact-checking organizations on WhatsApp during the 2022 Brazilian general election and compares them with content from Twitter and Kwai (a popular video-sharing application similar to TikTok). Given the democratic importance of accurate information during elections, multiple fact-checking organizations collaborated to collect and respond to misinformation via WhatsApp tiplines and power a fact-checking feature within a chatbot operated by Brazil’s election authority, the Tribunal Superior Eleitoral (TSE). We partnered with TSE and three fact-checking organizations and collected social media data to study how misinformation claims propagate across platforms. We observed little overlap between the users of different fact-checking tiplines and a high correlation between the number of users and the amount of unique content, suggesting that WhatsApp tiplines are far from reaching a saturation point. Similarly, we also found little overlap in content across platforms, indicating the need for further research with cross-platform approaches to identify misinformation dynamics.
AB - This study analyzes misinformation claims sent to fact-checking organizations on WhatsApp during the 2022 Brazilian general election and compares them with content from Twitter and Kwai (a popular video-sharing application similar to TikTok). Given the democratic importance of accurate information during elections, multiple fact-checking organizations collaborated to collect and respond to misinformation via WhatsApp tiplines and power a fact-checking feature within a chatbot operated by Brazil’s election authority, the Tribunal Superior Eleitoral (TSE). We partnered with TSE and three fact-checking organizations and collected social media data to study how misinformation claims propagate across platforms. We observed little overlap between the users of different fact-checking tiplines and a high correlation between the number of users and the amount of unique content, suggesting that WhatsApp tiplines are far from reaching a saturation point. Similarly, we also found little overlap in content across platforms, indicating the need for further research with cross-platform approaches to identify misinformation dynamics.
UR - http://www.scopus.com/inward/record.url?scp=85198298001&partnerID=8YFLogxK
U2 - 10.1093/ijpor/edae032
DO - 10.1093/ijpor/edae032
M3 - Article
AN - SCOPUS:85198298001
SN - 0954-2892
VL - 36
JO - International Journal of Public Opinion Research
JF - International Journal of Public Opinion Research
IS - 3
ER -