{"title":"推送可信信息作为应对错误信息的对策:来自推特的证据","authors":"Elina H. Hwang, Stephanie Lee","doi":"10.1287/isre.2021.0491","DOIUrl":null,"url":null,"abstract":"As people increasingly rely on social media to obtain healthcare information, misinformation, such as myths, rumors, and false information on healthcare, is posing a grave threat to public health. This paper investigates a potential remedy for such infodemic by examining a unique countermeasure that Twitter implemented. Instead of resorting to outright censorship, Twitter has taken a more nuanced approach: The platform has been nudging its users toward reputable sources whenever they seek out topics susceptible to misinformation. By analyzing the propagation of news articles that contain misinformation about health topics, we find that misinformation is less likely to initiate a diffusion process on Twitter since the inception of the policy. Moreover, tweets that include a link to misinformation articles are less likely to receive retweets, quotes, or replies. Furthermore, we find that the observed reduction is primarily driven by a decline in diffusion activities by human-like accounts rather than bot-like accounts. Our findings suggest that a misinformation policy that nudges platform users to a credible information source can help effectively curb misinformation diffusion. This approach may serve as a model for other platforms grappling with the challenge of misinformation in the digital age.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":"45 1","pages":""},"PeriodicalIF":5.0000,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Nudge to Credible Information as a Countermeasure to Misinformation: Evidence from Twitter\",\"authors\":\"Elina H. Hwang, Stephanie Lee\",\"doi\":\"10.1287/isre.2021.0491\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As people increasingly rely on social media to obtain healthcare information, misinformation, such as myths, rumors, and false information on healthcare, is posing a grave threat to public health. This paper investigates a potential remedy for such infodemic by examining a unique countermeasure that Twitter implemented. Instead of resorting to outright censorship, Twitter has taken a more nuanced approach: The platform has been nudging its users toward reputable sources whenever they seek out topics susceptible to misinformation. By analyzing the propagation of news articles that contain misinformation about health topics, we find that misinformation is less likely to initiate a diffusion process on Twitter since the inception of the policy. Moreover, tweets that include a link to misinformation articles are less likely to receive retweets, quotes, or replies. Furthermore, we find that the observed reduction is primarily driven by a decline in diffusion activities by human-like accounts rather than bot-like accounts. Our findings suggest that a misinformation policy that nudges platform users to a credible information source can help effectively curb misinformation diffusion. This approach may serve as a model for other platforms grappling with the challenge of misinformation in the digital age.\",\"PeriodicalId\":48411,\"journal\":{\"name\":\"Information Systems Research\",\"volume\":\"45 1\",\"pages\":\"\"},\"PeriodicalIF\":5.0000,\"publicationDate\":\"2024-02-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Information Systems Research\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1287/isre.2021.0491\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"INFORMATION SCIENCE & LIBRARY SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Systems Research","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1287/isre.2021.0491","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
A Nudge to Credible Information as a Countermeasure to Misinformation: Evidence from Twitter
As people increasingly rely on social media to obtain healthcare information, misinformation, such as myths, rumors, and false information on healthcare, is posing a grave threat to public health. This paper investigates a potential remedy for such infodemic by examining a unique countermeasure that Twitter implemented. Instead of resorting to outright censorship, Twitter has taken a more nuanced approach: The platform has been nudging its users toward reputable sources whenever they seek out topics susceptible to misinformation. By analyzing the propagation of news articles that contain misinformation about health topics, we find that misinformation is less likely to initiate a diffusion process on Twitter since the inception of the policy. Moreover, tweets that include a link to misinformation articles are less likely to receive retweets, quotes, or replies. Furthermore, we find that the observed reduction is primarily driven by a decline in diffusion activities by human-like accounts rather than bot-like accounts. Our findings suggest that a misinformation policy that nudges platform users to a credible information source can help effectively curb misinformation diffusion. This approach may serve as a model for other platforms grappling with the challenge of misinformation in the digital age.
期刊介绍:
ISR (Information Systems Research) is a journal of INFORMS, the Institute for Operations Research and the Management Sciences. Information Systems Research is a leading international journal of theory, research, and intellectual development, focused on information systems in organizations, institutions, the economy, and society.