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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. 

In an increasingly information-dense web, how do we ensure that we do not fall for unreliable information? To design better web literacy practices for assessing online information, we need to understand how people perceive the credibility of unfamiliar websites under time constraints. Would they be able to rate real news websites as more credible and fake news websites as less credible? We investigated this research question through an experimental study with 42 participants (mean age = 28.3) who were asked to rate the credibility of various “real news” (n = 14) and “fake news” (n = 14) websites under different time conditions (6s, 12s, 20s), and with a different advertising treatment (with or without ads). Participants did not visit the websites to make their credibility assessments; instead, they interacted with the images of website screen captures, which were modified to remove any mention of website names, to avoid the effect of name recognition. Participants rated the credibility of each website on a scale from 1 to 7 and in follow-up interviews provided justifications for their credibility scores. Through hypothesis testing, we find that participants, despite limited time exposure to each website (between 6 and 20 seconds), are quite good at the task of distinguishing between real and fake news websites, with real news websites being overall rated as more credible than fake news websites. Our results agree with the well-known theory of “first impressions” from psychology, that has established the human ability to infer character traits from faces. That is, participants can quickly infer meaningful visual and content cues from a website, that are helping them make the right credibility evaluation decision.