{"title":"NewsSlant：从道德视角分析政治新闻及其影响","authors":"Amanul Haque;Munindar P. Singh","doi":"10.1109/TCSS.2023.3341910","DOIUrl":null,"url":null,"abstract":"Political news is often slanted toward its publisher's ideology and seeks to influence readers by focusing on selected aspects of contentious social and political issues. We investigate political slants in news and their influence on readers by analyzing election-related news and readers’ reactions to the news on Twitter. To this end, we collected election-related news from six major U.S. news publishers who covered the 2020 U.S. presidential election. We computed each publisher's political slant based on the favorability of its news toward the two major parties’ presidential candidates. We find that the election-related news coverage shows signs of political slant both in news headlines and on Twitter. The difference in news coverage of the two candidates between the left-leaning (\n<sc>LEFT</small>\n) and right-leaning (\n<sc>RIGHT</small>\n) news publishers is statistically significant. The effect size is larger for the news on Twitter than for headlines. And, news on Twitter expresses stronger sentiments than the headlines. We identify moral foundations in readers’ reactions to the news on Twitter based on the moral foundation theory. Moral foundations in readers’ reactions to \n<sc>LEFT</small>\n and \n<sc>RIGHT</small>\n differ statistically significantly, though the effects are small. Further, these shifts in moral foundations differ across social and political issues. User engagement on Twitter is higher for \n<sc>RIGHT</small>\n than for \n<sc>LEFT</small>\n. We posit that an improved understanding of slant and influence can enable better ways to combat online political polarization.","PeriodicalId":13044,"journal":{"name":"IEEE Transactions on Computational Social Systems","volume":null,"pages":null},"PeriodicalIF":4.5000,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"NewsSlant: Analyzing Political News and Its Influence Through a Moral Lens\",\"authors\":\"Amanul Haque;Munindar P. Singh\",\"doi\":\"10.1109/TCSS.2023.3341910\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Political news is often slanted toward its publisher's ideology and seeks to influence readers by focusing on selected aspects of contentious social and political issues. We investigate political slants in news and their influence on readers by analyzing election-related news and readers’ reactions to the news on Twitter. To this end, we collected election-related news from six major U.S. news publishers who covered the 2020 U.S. presidential election. We computed each publisher's political slant based on the favorability of its news toward the two major parties’ presidential candidates. We find that the election-related news coverage shows signs of political slant both in news headlines and on Twitter. The difference in news coverage of the two candidates between the left-leaning (\\n<sc>LEFT</small>\\n) and right-leaning (\\n<sc>RIGHT</small>\\n) news publishers is statistically significant. The effect size is larger for the news on Twitter than for headlines. And, news on Twitter expresses stronger sentiments than the headlines. We identify moral foundations in readers’ reactions to the news on Twitter based on the moral foundation theory. Moral foundations in readers’ reactions to \\n<sc>LEFT</small>\\n and \\n<sc>RIGHT</small>\\n differ statistically significantly, though the effects are small. Further, these shifts in moral foundations differ across social and political issues. User engagement on Twitter is higher for \\n<sc>RIGHT</small>\\n than for \\n<sc>LEFT</small>\\n. We posit that an improved understanding of slant and influence can enable better ways to combat online political polarization.\",\"PeriodicalId\":13044,\"journal\":{\"name\":\"IEEE Transactions on Computational Social Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.5000,\"publicationDate\":\"2024-01-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Computational Social Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10379491/\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, CYBERNETICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Computational Social Systems","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10379491/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, CYBERNETICS","Score":null,"Total":0}
NewsSlant: Analyzing Political News and Its Influence Through a Moral Lens
Political news is often slanted toward its publisher's ideology and seeks to influence readers by focusing on selected aspects of contentious social and political issues. We investigate political slants in news and their influence on readers by analyzing election-related news and readers’ reactions to the news on Twitter. To this end, we collected election-related news from six major U.S. news publishers who covered the 2020 U.S. presidential election. We computed each publisher's political slant based on the favorability of its news toward the two major parties’ presidential candidates. We find that the election-related news coverage shows signs of political slant both in news headlines and on Twitter. The difference in news coverage of the two candidates between the left-leaning (
LEFT
) and right-leaning (
RIGHT
) news publishers is statistically significant. The effect size is larger for the news on Twitter than for headlines. And, news on Twitter expresses stronger sentiments than the headlines. We identify moral foundations in readers’ reactions to the news on Twitter based on the moral foundation theory. Moral foundations in readers’ reactions to
LEFT
and
RIGHT
differ statistically significantly, though the effects are small. Further, these shifts in moral foundations differ across social and political issues. User engagement on Twitter is higher for
RIGHT
than for
LEFT
. We posit that an improved understanding of slant and influence can enable better ways to combat online political polarization.
期刊介绍：
IEEE Transactions on Computational Social Systems focuses on such topics as modeling, simulation, analysis and understanding of social systems from the quantitative and/or computational perspective. "Systems" include man-man, man-machine and machine-machine organizations and adversarial situations as well as social media structures and their dynamics. More specifically, the proposed transactions publishes articles on modeling the dynamics of social systems, methodologies for incorporating and representing socio-cultural and behavioral aspects in computational modeling, analysis of social system behavior and structure, and paradigms for social systems modeling and simulation. The journal also features articles on social network dynamics, social intelligence and cognition, social systems design and architectures, socio-cultural modeling and representation, and computational behavior modeling, and their applications.
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