Zeve Sanderson, Megan A. Brown, Richard Bonneau, Jonathan Nagler, Joshua A. Tucker
{"title":"推特将唐纳德·特朗普的推文标记为选举错误信息:这些推文继续在平台内外传播","authors":"Zeve Sanderson, Megan A. Brown, Richard Bonneau, Jonathan Nagler, Joshua A. Tucker","doi":"10.37016/mr-2020-77","DOIUrl":null,"url":null,"abstract":"We analyze the spread of Donald Trump’s tweets that were flagged by Twitter using two intervention strategies—attaching a warning label and blocking engagement with the tweet entirely. We find that while blocking engagement on certain tweets limited their diffusion, messages we examined with warning labels spread further on Twitter than those without labels. Additionally, the messages that had been blocked on Twitter remained popular on Facebook, Instagram, and Reddit, being posted more often and garnering more visibility than messages that had either been labeled by Twitter or received no intervention at all. Taken together, our results emphasize the importance of considering content moderation at the ecosystem level.","PeriodicalId":93289,"journal":{"name":"Harvard Kennedy School misinformation review","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"Twitter flagged Donald Trump’s tweets with election misinformation: They continued to spread both on and off the platform\",\"authors\":\"Zeve Sanderson, Megan A. Brown, Richard Bonneau, Jonathan Nagler, Joshua A. Tucker\",\"doi\":\"10.37016/mr-2020-77\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We analyze the spread of Donald Trump’s tweets that were flagged by Twitter using two intervention strategies—attaching a warning label and blocking engagement with the tweet entirely. We find that while blocking engagement on certain tweets limited their diffusion, messages we examined with warning labels spread further on Twitter than those without labels. Additionally, the messages that had been blocked on Twitter remained popular on Facebook, Instagram, and Reddit, being posted more often and garnering more visibility than messages that had either been labeled by Twitter or received no intervention at all. Taken together, our results emphasize the importance of considering content moderation at the ecosystem level.\",\"PeriodicalId\":93289,\"journal\":{\"name\":\"Harvard Kennedy School misinformation review\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Harvard Kennedy School misinformation review\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.37016/mr-2020-77\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Harvard Kennedy School misinformation review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37016/mr-2020-77","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Twitter flagged Donald Trump’s tweets with election misinformation: They continued to spread both on and off the platform
We analyze the spread of Donald Trump’s tweets that were flagged by Twitter using two intervention strategies—attaching a warning label and blocking engagement with the tweet entirely. We find that while blocking engagement on certain tweets limited their diffusion, messages we examined with warning labels spread further on Twitter than those without labels. Additionally, the messages that had been blocked on Twitter remained popular on Facebook, Instagram, and Reddit, being posted more often and garnering more visibility than messages that had either been labeled by Twitter or received no intervention at all. Taken together, our results emphasize the importance of considering content moderation at the ecosystem level.