The ‘Fairness Doctrine’ lives on? Theorizing about the Algorithmic News Curation of Google’s Top Stories
When one searches for political candidates on Google, a panel composed of recent news stories, known as Top stories, is commonly shown at the top of the search results page. These stories are selected by an algorithm that chooses from hundreds of thousands of articles published by thousands of news publishers. In our previous work, we identified 56 news sources that contributed 2/3 of all Top stories for 30 political candidates running in the primaries of 2020 US Presidential Election. In this paper, we survey US voters to elicit their familiarity and trust with these 56 news outlets. We fi...- doi
- 10.1145/3372923.3404794
- name
- The ‘Fairness Doctrine’ lives on? Theorizing about the Algorithmic News Curation of Google’s Top Stories
- pages
- 10
- acm_url
- https://dl.acm.org/doi/10.1145/3372923.3404794
- authors
- Anna Kawakami, Khonzoda Umarova, Dongchen Huang, Eni Mustafaraj
- doi_url
- https://doi.org/10.1145/3372923.3404794
- license
- restricted
- summary
- When one searches for political candidates on Google, a panel composed of recent news stories, known as Top stories, is commonly shown at the top of the search results page. These stories are selected by an algorithm that chooses from hundreds of thousands of articles published by thousands of news publishers. In our previous work, we identified 56 news sources that contributed 2/3 of all Top stories for 30 political candidates running in the primaries of 2020 US Presidential Election. In this paper, we survey US voters to elicit their familiarity and trust with these 56 news outlets. We fi...
- keywords
- algorithmic news curation, media bias, elections, Google, survey
- source_pdf
- HT-2020_51-35_3372923/3372923.3404794.pdf
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- full_text
- open_access
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- ccs_concepts
- • Human-centered computing → Empirical studies in HCI;
- displayAuthor
- Anna Kawakami, Khonzoda Umarova, Dongchen Huang, Eni Mustafaraj
- source_attribution
- Formatting converted from the ACM version of record under supplied ACM publication authorization.
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