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1. The ‘Fairness Doctrine’ lives on? Theorizing about the Algorithmic News Curation of Google’s Top Stories

   https://doi.org/https://doi.org/10.1145/3372923.3404794  

   Kawakami, Anna; Umarova, Khonzoda; Huang, Dongchen; Mustafaraj, Eni (July 2020, The 31st ACM Conference on HyperText and Social Media)

   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 find that some of the most frequent outlets are not familiar to all voters (e.g. The Hill or Politico), or particularly trusted by voters of any political stripes (e.g. Washington Examiner or The Daily Beast). Why then, are such sources shown so frequently in Top stories? We theorize that Google is sampling news articles from sources with different political leanings to offer a balanced coverage. This is reminiscent of the so-called “fairness doctrine” (1949-1987) policy in the United States that required broadcasters (radio or TV stations) to air contrasting views about controversial matters. Because there are fewer right-leaning publications than center or left-leaning ones, in order to maintain this “fair” balance, hyper-partisan far-right news sources of low trust receive more visibility than some news sources that are more familiar to and trusted by the public. 

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2. The politics of identity: The unexpected role of political orientation on racial categorizations of Kamala Harris

   Ma, D. S. (June 2021, Analyses of social issues and public policy)

   null (Ed.)

   The 2020 US Presidential election was historic in that it featured the first woman of color, Kamala Harris, on a major-party ticket. Although Harris identifies as Black, her racial identity was widely scrutinized throughout the election, due to her mixed-race ancestry. Moreover, media coverage of Harris's racial identity appeared to vary based on that news outlet's political leaning and sometimes had prejudicial undertones. The current research investigated racial categorization of Harris and the role that political orientation and anti-Black prejudice might play in shaping these categorizations. Studies 1 and 2 tested the possibility that conservatives and liberals might mentally represent Harris differently, which we hypothesized would lead the two groups to differ in how they categorized her race. Contrary to our prediction, conservatives, and liberals mentally represented Harris similarly. Also surprising were the explicit racial categorization data. Conservatives labeled Harris as White more than liberals, who tended to categorize Harris as multiracial. This pattern was explained by anti-Black prejudice. Study 3 examined a potential political motivation that might explain this finding. We found that conservatives, more than liberals, judge having a non-White candidate on a Democratic ballot as an asset, which may lead conservatives to deny non-White candidates these identities. 

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3. Auditing Google's Search Headlines as a Potential Gateway to Misleading Content: Evidence from the 2020 US Election

   https://doi.org/10.54501/jots.v1i4.72  

   Zade, Himanshu; Wack, Morgan; Zhang, Yuanrui; Starbird, Kate; Calo, Ryan; Young, Jason; West, Jevin D. (September 2022, Journal of Online Trust and Safety)

   The prevalence and spread of online misinformation during the 2020 US presidential election served to perpetuate a false belief in widespread election fraud. Though much research has focused on how social media platforms connected people to election-related rumors and conspiracy theories, less is known about the search engine pathways that linked users to news content with the potential to undermine trust in elections. In this paper, we present novel data related to the content of political headlines during the 2020 US election period. We scraped over 800,000 headlines from Google's search engine results pages (SERP) in response to 20 election-related keywords—10 general (e.g., "Ballots") and 10 conspiratorial (e.g., "Voter fraud")—when searched from 20 cities across 16 states. We present results from qualitative coding of 5,600 headlines focused on the prevalence of delegitimizing information. Our results reveal that videos (as compared to stories, search results, and advertisements) are the most problematic in terms of exposing users to delegitimizing headlines. We also illustrate how headline content varies when searching from a swing state, adopting a conspiratorial search keyword, or reading from media domains with higher political bias. We conclude with policy recommendations on data transparency that allow researchers to continue to monitor search engines during elections. 

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4. Headline Format Influences Evaluation of, but Not Engagement with, Environmental News

   https://doi.org/10.1080/17512786.2020.1805794  

   Janét, Kristina; Richards, Othello; Landrum, Asheley R. (January 2020, Journalism Practice)

   Sparked by a collaboration between academic researchers and science media professionals, this study sought to test three commonly used headline formats that vary based on whether (and, if so, how) important information is left out of a headline to encourage participants to read the corresponding article; these formats are traditionally-formatted headlines, forward-referencing headlines, and question-based headlines. Although headline format did not influence story selection or engagement, it did influence participants evaluations of both the headline’s and the story’s credibility (question-based headlines were viewed as the least credible). Moreover, individuals’ science curiosity and political views predicted their engagement with environmental stories as well as their views about the credibility of the headline and story. Thus, headline formats appear to play a significant role in audience’s perceptions of online news stories, and science news professionals ought to consider the effects different formats have on readers. 

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5. The Media Coverage of the 2020 US Presidential Election Candidates through the Lens of Google’s Top Stories

   Kawakami, Anna; Umarova, Khonzoda; Mustafaraj, Eni (June 2020, The 14th International AAAI Conference on Web and Social Media (ICWSM 2020))

   Choosing the political party nominees, who will appear on the ballot for the US presidency, is a long process that starts two years before the general election. The news media plays a particular role in this process by continuously covering the state of the race. How can this news coverage be characterized? Given that there are thousands of news organizations, but each of us is exposed to only a few of them, we might be missing most of it. Online news aggregators, which aggregate news stories from a multitude of news sources and perspectives, could provide an important lens for the analysis. One such aggregator is Google’s Top stories, a recent addition to Google’s search result page. For the duration of 2019, we have collected the news headlines that Google Top stories has displayed for 30 candidates of both US political parties. Our dataset contains 79,903 news story URLs published by 2,168 unique news sources. Our analysis indicates that despite this large number of news sources, there is a very skewed distribution of where the Top stories are originating, with a very small number of sources contributing the majority of stories. We are sharing our dataset1 so that other researchers can answer questions related to algorithmic curation of news as well as media agenda setting in the context of political elections. 

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