Subscriptions and external links help drive resentful users to alternative and extremist YouTube channels.

Do online platforms facilitate the consumption of potentially harmful content? Using paired behavioral and survey data provided by participants recruited from a representative sample in 2020 (n = 1181), we show that exposure to alternative and extremist channel videos on YouTube is heavily concentrated among a small group of people with high prior levels of gender and racial resentment. These viewers often subscribe to these channels (prompting recommendations to their videos) and follow external links to them. In contrast, nonsubscribers rarely see or follow recommendations to videos from these channels. Our findings suggest that YouTube's algorithms were not sending people down "rabbit holes" during our observation window in 2020, possibly due to changes that the company made to its recommender system in 2019. However, the platform continues to play a key role in facilitating exposure to content from alternative and extremist channels among dedicated audiences.

Challenges in Understanding Human-Algorithm Entanglement During Online Information Consumption.

Most content consumed online is curated by proprietary algorithms deployed by social media platforms and search engines. In this article, we explore the interplay between these algorithms and human agency. Specifically, we consider the extent of entanglement or coupling between humans and algorithms along a continuum from implicit to explicit demand. We emphasize that the interactions people have with algorithms not only shape users' experiences in that moment but because of the mutually shaping nature of such systems can also have longer-term effects through modifications of the underlying social-network structure. Understanding these mutually shaping systems is challenging given that researchers presently lack access to relevant platform data. We argue that increased transparency, more data sharing, and greater protections for external researchers examining the algorithms are required to help researchers better understand the entanglement between humans and algorithms. This better understanding is essential to support the development of algorithms with greater benefits and fewer risks to the public.

Users choose to engage with more partisan news than they are exposed to on Google Search.

If popular online platforms systematically expose their users to partisan and unreliable news, they could potentially contribute to societal issues such as rising political polarization1,2. This concern is central to the 'echo chamber'3-5 and 'filter bubble'6,7 debates, which critique the roles that user choice and algorithmic curation play in guiding users to different online information sources8-10. These roles can be measured as exposure, defined as the URLs shown to users by online platforms, and engagement, defined as the URLs selected by users. However, owing to the challenges of obtaining ecologically valid exposure data-what real users were shown during their typical platform use-research in this vein typically relies on engagement data4,8,11-16 or estimates of hypothetical exposure17-23. Studies involving ecological exposure have therefore been rare, and largely limited to social media platforms7,24, leaving open questions about web search engines. To address these gaps, we conducted a two-wave study pairing surveys with ecologically valid measures of both exposure and engagement on Google Search during the 2018 and 2020 US elections. In both waves, we found more identity-congruent and unreliable news sources in participants' engagement choices, both within Google Search and overall, than they were exposed to in their Google Search results. These results indicate that exposure to and engagement with partisan or unreliable news on Google Search are driven not primarily by algorithmic curation but by users' own choices.

Estimates of Non-Heterosexual Prevalence: The Roles of Anonymity and Privacy in Survey Methodology.

When do people feel comfortable enough to provide honest answers to sensitive questions? Focusing specifically on sexual orientation prevalence-a measure that is sensitive to the pressures of heteronormativity-the present study was conducted to examine the variability in U.S. estimates of non-heterosexual identity prevalence and to determine how comfortable people are with answering questions about their sexual orientation when asked through commonly used survey modes. We found that estimates of non-heterosexual prevalence in the U.S. increased as the privacy and anonymity of the survey increased. Utilizing an online questionnaire, we rank-ordered 16 survey modes by asking people to rate their level of comfort with each mode in the context of being asked questions about their sexual orientation. A demographically diverse sample of 652 individuals in the U.S. rated each mode on a scale from -5 (very uncomfortable) to +5 (very comfortable). Modes included anonymous (name not required) and non-anonymous (name required) versions of questions, as well as self-administered and interviewer-administered versions. Subjects reported significantly higher mean comfort levels with anonymous modes than with non-anonymous modes and significantly higher mean comfort levels with self-administered modes than with interviewer-administered modes. Subjects reported the highest mean comfort level with anonymous online surveys and the lowest with non-anonymous personal interviews that included a video recording. Compared with the estimate produced by an online survey with a nationally representative sample, surveys utilizing more intrusive methodologies may have underestimated non-heterosexual prevalence in the U.S. by between 50 and 414%. Implications for public policy are discussed.

The search engine manipulation effect (SEME) and its possible impact on the outcomes of elections.

Internet search rankings have a significant impact on consumer choices, mainly because users trust and choose higher-ranked results more than lower-ranked results. Given the apparent power of search rankings, we asked whether they could be manipulated to alter the preferences of undecided voters in democratic elections. Here we report the results of five relevant double-blind, randomized controlled experiments, using a total of 4,556 undecided voters representing diverse demographic characteristics of the voting populations of the United States and India. The fifth experiment is especially notable in that it was conducted with eligible voters throughout India in the midst of India's 2014 Lok Sabha elections just before the final votes were cast. The results of these experiments demonstrate that (i) biased search rankings can shift the voting preferences of undecided voters by 20% or more, (ii) the shift can be much higher in some demographic groups, and (iii) search ranking bias can be masked so that people show no awareness of the manipulation. We call this type of influence, which might be applicable to a variety of attitudes and beliefs, the search engine manipulation effect. Given that many elections are won by small margins, our results suggest that a search engine company has the power to influence the results of a substantial number of elections with impunity. The impact of such manipulations would be especially large in countries dominated by a single search engine company.