Search engine effects on news consumption: Ranking and representativeness outweigh familiarity in news selection

While individuals' trust in search engine results is well-supported, little is known about their preferences when selecting news. We use web-tracked behavioral data across a 2-month period (280 participants) and we analyze three competing factors, two algorithmic (ranking and representativeness) and one psychological (familiarity), that could influence the selection of search results. We use news engagement as a proxy for familiarity and investigate news articles presented on Google search pages (n = 1221). We find a significant effect of algorithmic factors but not of familiarity. We find that ranking plays a lesser role for news compared to non-news, suggesting a more careful decision-making process. We confirm that Google Search drives individuals to unfamiliar sources, and find that it increases the diversity of the political audience of news sources. We tackle the challenge of measuring social science theories in contexts shaped by algorithms, demonstrating their leverage over the behaviors of individuals

Do Athletes Imagine Being the Best, or Crossing the Finish Line First? A Mixed Methods Analysis of Construal Levels in Elite Athletes' Spontaneous Imagery

The purpose of this article is to illustrate data transformation in a mixed methods research phenomenological study, investigating how athletes use concrete and abstract spontaneous imagery in and around competition. To achieve this, we combined the application of co-occurring codes and numerical transformation in a novel way. A thematic analysis of qualitative interviews with 12 elite athletes identified concrete imagery to focus on strategy generation, error correction, technique, and preparation, and abstract imagery to focus on desirability, symbolic and verbal representations, and regulation of affect, arousal, and mastery. Statistical analysis identified that subjective effectiveness of imagery significantly differed for sport type (reactive/static) and competition times. Researchers wishing to apply statistical analyses to qualitative data are encouraged to employ our methodology

Who are the users of ChatGPT? Implications for the digital divide from web tracking data

A major challenge of our time is reducing disparities in access to and effective use of digital technologies, with recent discussions highlighting the role of AI in exacerbating the digital divide. We examine user characteristics that predict usage of the AI-powered conversational agent ChatGPT. We combine web tracking and survey data of N=1068 German citizens to investigate differences in activity (usage, visits and duration on chat.openai.com). We examine socio-demographics commonly associated with the digital divide and explore further socio-political attributes identified via stability selection in Lasso regressions. We confirm lower age and more education to affect ChatGPT usage, but not gender and income. We find full-time employment and more children to be barriers to ChatGPT activity. Rural residence, writing and social media activities, as well as more political knowledge, were positively associated with ChatGPT activity. Our research informs efforts to address digital disparities and promote digital literacy among underserved populations

Representativeness and face-ism: Gender bias in image search

Implicit and explicit gender biases in media representations of individuals have long existed. Women are less likely to be represented in gender-neutral media content (representation bias), and their face-to-body ratio in images is often lower (face-ism bias). In this article, we look at representativeness and face-ism in search engine image results. We systematically queried four search engines (Google, Bing, Baidu, Yandex) from three locations, using two browsers and in two waves, with gender-neutral (person, intelligent person) and gendered (woman, intelligent woman, man, intelligent man) terminology, accessing the top 100 image results. We employed automatic identification for the individual’s gender expression (female/male) and the calculation of the face-to-body ratio of individuals depicted. We find that, as in other forms of media, search engine images perpetuate biases to the detriment of women, confirming the existence of the representation and face-ism biases. In-depth algorithmic debiasing with a specific focus on gender bias is overdue

Institutions and Cultural Diversity: Effects of Democratic and Propaganda Processes on Local Convergence and Global Diversity

<div><p>In a connected world where people influence each other, what can cause a globalized monoculture, and which measures help to preserve the coexistence of cultures? Previous research has shown that factors such as homophily, population size, geography, mass media, and type of social influence play important roles. In the present paper, we investigate for the first time the impact that institutions have on cultural diversity. In our first three studies, we extend existing agent-based models and explore the effects of institutional influence and agent loyalty. We find that higher institutional influence increases cultural diversity, while individuals' loyalty to their institutions has a small, preserving effect. In three further studies, we test how bottom-up and top-down processes of institutional influence impact our model. We find that bottom-up democratic practices, such as referenda, tend to produce convergence towards homogeneity, while top-down information dissemination practices, such as propaganda, further increase diversity. In our last model—an integration of bottom-up and top-down processes into a feedback loop of information—we find that when democratic processes are rare, the effects of propaganda are amplified, i.e., more diversity emerges; however, when democratic processes are common, they are able to neutralize or reverse this propaganda effect. Importantly, our models allow for control over the full spectrum of diversity, so that a manipulation of our parameters can result in preferred levels of diversity, which will be useful for the study of other factors in the future. We discuss possible mechanisms behind our results, applications, and implications for political and social sciences.</p></div

Contrasting factors for experiments A to F.

<p>Contrasting factors for experiments A to F.</p

Cultural diversity for combinations of democracy and propaganda frequencies.

<p>X-axis displays levels of noise; Y-axis displays normalized cultural diversity. Each line symbol denotes one combination of democracy and propaganda. 95% confidence intervals are displayed only when exceeding the size of the line symbol. Data points are averages of 50 repetitions per territory with 100,000 iterations per agent.</p

Number of cultures and institutions (cultures / institutions) per population size over alpha values 0.5 to 0.95.

<p>Number of cultures and institutions (cultures / institutions) per population size over alpha values 0.5 to 0.95.</p