{"title":"新闻分享是衡量媒体一致性的一种方式","authors":"Gábor Simonovits, Ádám Vig","doi":"10.51685/jqd.2023.010","DOIUrl":null,"url":null,"abstract":"In this note we introduce a new approach to measure media alignment derived from the story-sharing behavior of journalists. We use a large corpus of online news stories from two leading Hungarian news sites and estimate alignment scores for a large number of outlets that they cite. To the extent that journalists are more likely to cite ideologically proximate sources, our measure can be used to compare a large number of media outlets on a political — in our case government vs. independent — space. We demonstrate the use of this approach with two empirical applications. First, we show that our alignment scores successfully capture known ideological variation across outlets at a single point in time. Second, we demonstrate that quarterly estimates of alignment for a captured outlet change dramatically following an abrupt change in ownership.","PeriodicalId":93587,"journal":{"name":"Journal of quantitative description: digital media","volume":"18 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"News sharing as a measure of media alignment\",\"authors\":\"Gábor Simonovits, Ádám Vig\",\"doi\":\"10.51685/jqd.2023.010\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this note we introduce a new approach to measure media alignment derived from the story-sharing behavior of journalists. We use a large corpus of online news stories from two leading Hungarian news sites and estimate alignment scores for a large number of outlets that they cite. To the extent that journalists are more likely to cite ideologically proximate sources, our measure can be used to compare a large number of media outlets on a political — in our case government vs. independent — space. We demonstrate the use of this approach with two empirical applications. First, we show that our alignment scores successfully capture known ideological variation across outlets at a single point in time. Second, we demonstrate that quarterly estimates of alignment for a captured outlet change dramatically following an abrupt change in ownership.\",\"PeriodicalId\":93587,\"journal\":{\"name\":\"Journal of quantitative description: digital media\",\"volume\":\"18 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of quantitative description: digital media\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.51685/jqd.2023.010\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of quantitative description: digital media","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.51685/jqd.2023.010","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this note we introduce a new approach to measure media alignment derived from the story-sharing behavior of journalists. We use a large corpus of online news stories from two leading Hungarian news sites and estimate alignment scores for a large number of outlets that they cite. To the extent that journalists are more likely to cite ideologically proximate sources, our measure can be used to compare a large number of media outlets on a political — in our case government vs. independent — space. We demonstrate the use of this approach with two empirical applications. First, we show that our alignment scores successfully capture known ideological variation across outlets at a single point in time. Second, we demonstrate that quarterly estimates of alignment for a captured outlet change dramatically following an abrupt change in ownership.