Search

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. [ABSTRACT FROM AUTHOR]

This study introduces methods for identifying search directives—content that could prompt an online search—and explores their presence on social media. Search directives can be an effective tool for indirect online influence, because instead of guiding people directly to content (e.g., a news article), they indirectly guide people to it through an independent intermediary (e.g., Google Search). By directing viewers to “do their own research” on a known, trusted, or seemingly objective intermediary, search directives have advantages in terms of both persuasion, by making people feel as if they discovered the content on their own, and evasion, by not directly posting the target link(s). Here we present a framework for identifying search directives on social media that includes methods for automated discovery, classification, and query extraction. Data we collected from social media demonstrate the widespread use of search directives, provide construct validity for our definition, and support our framing of search directives as a form of indirect online influence. Last, we report three case studies that highlight the immediate value of identifying search directives to researchers, practitioners, and journalists focused on online trust and safety. [ABSTRACT FROM AUTHOR]

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.Ecologically valid data collected during the 2018 and 2020 US elections show 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. [ABSTRACT FROM AUTHOR]

In 2007, a comprehensive mental health referral inventory based on the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) was posted online as an alternative to the informal tests the public now uses to self-diagnose mental health problems. A validation study was published in 2011 (Epstein & Muzzatti, 2011). In 2013, a revision of that inventory that was consistent with the DSM-5 was posted. The present study evaluates the new inventory with a diverse sample of 201,625 people from 184 countries (mainly the United States, Canada, and the United Kingdom). The 63-item inventory screens for 21 common problems and typically takes about 5 min to complete. Test scores proved to be good predictors of a variety of self-reported criterion measures, including happiness, personal and professional success, history of hospitalization, history of therapy, current participation in therapy, and employment. Females were found to have slightly more mental health problems than males, and effects were also found for education and race/ethnicity. The revised test is more accessible than the original, reducing the reading level from grade 10.2 to 6.6. It is not designed to diagnose; rather, its primary purpose is to refer people to mental health professionals for further evaluation. It can also be used in clinical settings for quick screening purposes. [ABSTRACT FROM PUBLISHER]

In a large-scale follow-up to a recently published study, data obtained from 25,507 subjects in 58 countries (mainly the United States and Canada) were analyzed in an attempt to rank order seven important relationship competencies. In both studies, two competencies—communication and knowledge of partner—proved to be the strongest predictors of self-reported satisfaction in current relationships, a finding that might help provide some guidance for relationship education and therapy. Although both studies showed little differences overall between the relationship skills of males and females—that is, only small, nonsignificant differences in total scores obtained on the testing instrument—both studies found clear differences in the kinds of skills males and females bring to intimate relationships, a finding that is consistent with the findings of other studies. Effects were also found for race, education, and sexual orientation but not for age or country of residence. [ABSTRACT FROM PUBLISHER]

First proposed by Epstein, McKinney, Fox, and Garcia (2012), sexual orientation range (SOR) is an objective continuous measure of the flexibility people have in expressing their sexual orientation. In the present article, three formulas for computing SOR are compared using data obtained from a sample of 54,834 people in 57 countries. A number of statistical measures suggest that SOR is best measured simply as the smaller of two raw scores indicating opposite-sex and same-sex sexual inclinations. In other words, if one's strongest inclinations are same-sex, one's sexual orientation range is best indicated by the strength of one's opposite-sex inclinations, and vice versa. SOR, in combination with mean sexual orientation, another continuous variable, provides a reasonable and useful characterization of sexual orientation, which is and always has been a continuous rather than a categorical phenomenon. The SOR concept also puts the rancorous “choice” debate into an objective, non-inflammatory context. [ABSTRACT FROM PUBLISHER]

The article offers information on concerns about technology platforms, particularly YouTube, playing a role in exposing users to dubious and harmful content due to algorithmic recommendations. The study investigates the size and composition of the audience for potentially harmful content on YouTube and finds that such content is primarily consumed by a small minority with high levels of gender and racial resentment, and recommendations to this content.