意识形态
选择(遗传算法)
政治学
互联网隐私
生物
计算机科学
政治
人工智能
法学
作者
Frank Mangold,David Schoch,Sebastian Stier
出处
期刊:Science Advances
[American Association for the Advancement of Science (AAAS)]
日期:2024-09-13
卷期号:10 (37)
标识
DOI:10.1126/sciadv.adg9287
摘要
Today’s high-choice digital media environments allow citizens to completely refrain from online news exposure and, if they do use news, to select sources that align with their ideological preferences. Yet due to measurement problems and cross-country differences, recent research has been inconclusive regarding the prevalence of ideological self-selection into like-minded online news. We introduce a multi-method design combining the web-browsing histories and survey responses of more than 7000 participants from six major democracies with supervised text classification to separate political from nonpolitical news exposure. We find that political online news exposure is both substantially less prevalent and subject to stronger ideological self-selection than nonpolitical online news exposure, especially in the United States. By highlighting the peculiar role of political news content, the results improve the understanding of online news exposure and the role of digital media in democracy.
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