đŸ€– Must-Read Articles đŸ€–

Experimental Feature

Even just looking backwards a week, there are a lot more articles published than most of us could hope to read. We can always skim the titles and abstracts ourselves, but I wanted to test out some automation. The articles below, all of which can be found elsewhere on this site among other new publications, were chosen by Google Gemini Flash Thinking as "must-read" articles. The proper criteria are in the eyes of the beholder and Gemini doesn't apply my criteria without error. I may continue to refine the prompting based on experience and feedback. Like the rest of the site, this will update daily!

Does fact-checking influence media trust? Longitudinal evidence from Flanders
European Journal of Communication
Ferre Wouters, Lucie Wittner Franckx, Brahim Zarouali, Michaël Opgenhaffen
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Fact-checking is vital in combating misinformation, yet concerns persist regarding potential unintended effects on media trust. This study investigates causal dynamics between exposure to fact-checks and media trust over time, using a random intercept cross-lagged panel model (RI-CLPM) with longitudinal panel data from Flanders (Belgium) across three waves in 6 months before the 2024 elections. Findings indicate that people who encounter more fact-checks are also more likely to have higher trust in media. However, we found no causal relationship, suggesting that fact-checking neither erodes nor enhances media trust over time. Amid growing scrutiny of fact-checking by political actors and technology platforms, these results challenge assumptions about negative spillover effects of fact-checking.
Can fictional stories beat the congeniality bias? Selective exposure to fiction and non-fiction
Human Communication Research
Markus Appel, Juliane Gabel, Lena Wimmer, Marieke Klöppel, Tobias Richter
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People prefer attitude-consistent information over attitude-inconsistent information (congeniality bias). Connecting theory on the processing of stories to selective exposure theory, we assumed that the congeniality bias is reduced or even nullified when it comes to fictional messages. Across two experiments examining two different, polarizing topics (refugees, N1 = 1,326; theistic faith, N2 = 1,316) a highly consistent pattern of results could be observed: Participants were more willing to read a narrative message (exposure preference) in which the story events were in line with their attitudes rather than a message contrasting attitudes. This congeniality bias was unaffected by the fictionality of the information (i.e., whether the events were introduced as a fictional short story or a non-fictional journalistic reportage). Interestingly, the congeniality bias emerged for positive characterizations of refugees or theistic faith but not for negative characterizations. Implications regarding the role of fictionality and congeniality in selective exposure are discussed.
Toward a group theory of political communication
Journal of Communication
Stewart M Coles, Daniel Kreiss, Daniel S Lane, Shannon C McGregor
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Recent political communication scholarship finds that groups and identities play a central role in the crises faced by political and media systems globally, particularly in democracies. Yet an individualist orientation in the literature has resulted in key theoretical and conceptual limitations, preventing a broader group-centric theoretical framework from emerging. We synthesize disparate bodies of theory on groups, politics, and communication to offer three basic propositions underlying a group theory of political communication. First, it is the group—not the individual—that is the fundamental organizing unit of social and political life. Second, groups are constituted through communication, which is central to how they define their politics. Third, groups and politics are reciprocally influencing forces through political communication, oriented around power. We offer a framework for studying the role of groups in political communication at the micro, meso, and macro levels, providing a concrete agenda for the study of groups in political communication.
Beyond Credibility: The Effects of Different Forms of Visual Disinformation
Journalism & Mass Communication Quarterly
Teresa Weikmann, Jana Laura Egelhofer, Sophie Lecheler
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Deepfakes dominate discussions about manipulated videos, but other forms of visual disinformation are more prevalent and less understood. Moreover, deception is often assessed through measuring credibility, overlooking cognitive effects like misperceptions and attitude changes. To address these gaps, an online experiment ( N = 802) examined visual disinformation’s effects on credibility, misperceptions, and perceptions of a politician. The study compared a deepfake (machine learning manipulation), a cheapfake (rudimentary manipulation), and a decontextualized video (false context), all portraying the same politician and false message. Despite low in credibility, the deepfake and cheapfake caused a misperception, with the deepfake harming perceptions of the politician.
Immunizing the Public Against AI-Generated Disinformation: Testing the Effects of Inoculation Mode and Issue Attitude on Inoculation Likelihood of Political Deepfakes
Journalism & Mass Communication Quarterly
Bingbing Zhang, Sang Jung Kim, Alex Scott
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Political deepfakes are considered detrimental to democracy by eroding public trust and distorting communication. Scholars have advocated for inoculation strategies to counter deepfakes, yet they have found that individuals’ partisan attitudes can undermine the effects of inoculation. Guided by inoculation theory and motivated reasoning theory, we conducted a 3 (Inoculation Mode: Passive vs. Active vs. No Inoculation) × 2 (Deepfake Attack: Pro-Attitudinal vs. Counter-Attitudinal) between-subjects experiment. Results show that inoculation increases deepfake awareness, intention to debunk deepfakes, and information-seeking behaviors, while reducing the perceived credibility of deepfake messages. However, exposure to counter-attitudinal deepfakes led to greater agreement with embedded disinformation.
Deepfakes’ Cognitive, Emotional, and Behavioral Impact: A Systematic Review and Meta-Analysis of Individual Responses
Journalism & Mass Communication Quarterly
Seok Kang, Kayla Valadez
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This meta-analysis examines 24 experimental studies on deepfake effects on credibility, emotions, and sharing intention, comprising 20,685 participants from 10 countries. Moderator effects of media literacy, control type, video topic, literacy type, gender, age, and country on individual responses were also analyzed. Effect sizes indicated deepfakes’ impact on elevated emotions. Media literacy moderated the effects of deepfake exposure on diminished credibility and sharing intention. The moderator effect of no literacy on emotions was positive. The results suggest that critical media consumers with media literacy, depending on the topic and type, can mitigate the adverse effects of deepfakes.
From Intentional Avoidance to Estrangement? A Longitudinal Study of News Avoidance and News Media Repertoires in Sweden
Mass Communication and Society
Kiki de Bruin, Erik Espeland, Rens Vliegenthart, Jesper StrömbÀck
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Reconceptualising political influencers: An alternative means of definition and analysis
New Media & Society
Elizabeth Dubois, Katharine Dommett
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Recent interest in online political influencers has resulted in an array of competing definitions of who counts as a political influencer. Contending the value of a more porous and resilient definition able to recognise a spectrum of online political influence, we interrogate scholarship on opinion leadership, influentials, micro-celebrities, and social media influencer studies to reveal a range of identifying traits that can characterise different types of political influencers. Introducing a new approach to categorising these varied manifestations, we discuss six key attributes: personalised communication, compensation, audience size, political topical focus, control, and formal political role. Showing how this approach can be deployed to capture different manifestations of political influencers, we aim to build understanding that is resilient to change over time and that can support comparative empirical work.
Performative Propaganda Engagement: How Celebrity Fans Engage with State Propaganda on Weibo
Political Communication
Yingdan Lu
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The Limits of Computational Propaganda: Investigating Underexplored Platforms and Contexts
Political Communication
Hossein Kermani, Taberez Ahmed Neyazi, Sophie Lecheler
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Communicating About and Through Platform Values: Legitimizing Public Expression Regulation on X and Weibo 2007–2024
Social Media + Society
Tianchan Mao, Chris Chao Su, Ngai Keung Chan, Lei Guo
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In this article, we argue that social media platforms communicate their governance strategies both about and through values across diverse sites of communication— about values in presenting normative ideals and through values to justify their content moderation practices. Moreover, we highlight the significance of analyzing platform values across temporal and regional contexts, especially beyond the Western sphere. Focusing on X and Weibo, we employed content and network analysis to examine how they articulated values in different venues to regulate public expression from 2007 to 2024. Our findings reveal an increasing convergence in how the two platforms communicate about values in their community guidelines, suggesting a trend of institutional isomorphism in response to shared challenges such as misinformation and online safety. However, they diverged in communicating through values in administrative posts. While X emphasized personal-level values such as self-expression, Weibo prioritized social-level values, particularly social and political security, often in the context of addressing concrete cases.
History and Contrarian Expression: Debating Genocide on Reddit
Social Media + Society
Aliaksandr Herasimenka, Ralph Schroeder
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Social media communities are increasingly considered as spaces where evidence-based information about history is undermined. We combine expert interviews and content analysis of debates about genocide in a popular online contrarian community to understand how to mitigate the spread of misleading information across such communities in the domain of history. We analyse 1725 entries on 10 Reddit forums dedicated to debating and promoting scepticism towards international consensus about prominent historical topics. The entries we analyse cover three topics referred to as genocide by forum members: the Holocaust, the Holodomor, and the COVID-19 vaccination. The prevailing view suggests that contrarian expression fosters smaller, ideologically homogeneous, and relatively radical online spaces where differing views are diminished or entirely absent. To the contrary, we analyse real-life behavioural data to demonstrate substantial scepticism towards contrarian narratives even in some of the most popular dedicated online communities, which may suggest that these spaces are more internally contested than prevailing theories imply.
Linking Social Media News Use, AI Interest, and Political Ideology With AI Subjective Knowledge: A Moderated Mediation Model Across Two Countries
Social Media + Society
Manuel Goyanes, Hui Min Lee, Rebecca Scheffauer, Homero Gil de ZĂșñiga
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Social media has emerged as a pivotal platform for accessing news content today. While there appears to be a connection between news consumption on social media platforms and perceived knowledge of public affairs, little is known about the potential effect on specific issues like artificial intelligence (AI). To extend findings on people’s perceived knowledge of AI, how it relates to social media news consumption, and what other factors can contribute, we offer results based on original survey data from two societies (Germany, N = 2213, and Spain, N = 2337). This study advances a moderated mediation model by which social media news positively predicts heightened AI interest, which in turn is associated with increased AI subjective knowledge. This effect is significant for both conservatives and liberals, albeit stronger for conservatives.
A drag on the ticket? Estimating top‐of‐the‐ticket effects on down‐ballot races
American Journal of Political Science
Kevin DeLuca, Daniel J. Moskowitz, Benjamin Schneer
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Campaign staff, journalists, and political scientists commonly attribute the poor performances of a party's down‐ballot candidates to low‐quality or extreme top‐of‐the‐ticket candidates, but empirical evidence on this conventional wisdom is scant. We estimate the effect of candidate quality and ideology in gubernatorial and U.S. Senate elections on co‐partisan vote shares in down‐ballot U.S. House races. While naive estimates imply that top‐of‐the‐ticket candidates influence down‐ballot outcomes, after accounting for correlations in candidate quality/ideology across offices, we estimate near‐zero statewide top‐of‐the‐ticket effects on U.S. House elections. We similarly observe near‐zero top‐of‐the‐ticket effects in the further‐down‐ballot settings of state‐legislative and county‐legislative elections. Overall, voters exhibit a strong capacity to discern differences in quality and ideology across offices and incorporate this information into their vote choice throughout the time period under investigation. However, in line with other research, this link between candidate quality/ideology and election outcomes has weakened considerably in recent years.
Causal Inference, Agency, and the Problem of Inherent Endogeneity
Annual Review of Political Science
Martin J. Williams
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Researchers often leverage exogenous variation in an independent variable in order to understand its effects, yet endogenous decision processes are central to many of the real-world phenomena we wish to understand. This review explores whether there are situations in which exogenous and endogenous variation in the same independent variable (e.g., a policy, treatment, or other action) may lead to different outcomes. I begin by laying out a conceptual framework for understanding these inherently endogenous causal processes, identifying three types of mechanisms through which they might arise and discussing their application to a range of empirical phenomena, such as institutional reform, community natural resource governance, and interstate conflict. I then suggest that learning about inherently endogenous causal processes requires researchers to place endogenous decision-making at the center of analysis rather than seeking to abstract away from it. I survey a range of methods (both positivist and nonpositivist) for doing so.
Affective States: Cultural and Affective Polarization in a Multilevel-Multiparty System
Political Behavior
Dylan Paltra, Marius SĂ€ltzer, Christian Stecker
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Affective Polarization—the growing mutual dislike among partisan groups—has been identified as a major concern in democracies. Although both economic and cultural ideological divides contribute to ideological polarization, their affective consequences can differ. This paper argues that cultural polarization becomes especially consequential when mobilized by far-right parties. Using data from 116 elections in Germany’s 16 states (1990-2023), we combine more than 550 state-level manifestos with more than 150,000 survey responses to examine how party polarization translates into voter affect. Our analyses show that both economic and cultural polarization increase affective divides, but cultural disagreements fuel hostility only in the presence of the Alternative for Germany (AfD). Acting as a cultural entrepreneur, the AfD amplifies the emotional impact of cultural divisions such as immigration, employing affective rhetoric and provoking strong rejection from other parties and voters. These findings highlight the catalytic role of far-right parties in transforming ideological competition into affective polarization.
The psychology of political attitudinal volatility
Political Psychology
James Dennison
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The assumption that political beliefs are formed by early‐life socialization and psychological predispositions, leading to stability in adulthood, increasingly acts as a theoretical cornerstone in the literature. However, politics is replete with examples of attitudinal change; this article proposes that certain stable psychological predispositions are likely to foster volatility in attitudes and general cognition. Using British electoral panel data, it shows that social distrust, open‐mindedness, and tolerance for uncertainty are associated with greater volatility in attitudes to immigration, redistribution, European integration, environmentalism, capital punishment, and Scottish independence. Locus of control, need‐for‐cognition, empathy, and risk tolerance are associated only with volatility in attitudes to some issues. Age, education, household income, being male, and lower partisanship are all negatively associated with attitudinal volatility. Overall, this study suggests that attitudinal volatility itself constitutes a meaningful dimension of political behavior, rooted in stable psychological predispositions.
An Audit of Social Science Survey Experiments
Public Opinion Quarterly
Tamkinat Rauf, Jan Gerrit Voelkel, James Druckman, Jeremy Freese
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Survey experiments have become a popular methodology for causal inference across the social sciences. We study the efficacy of survey experiment designs by analyzing 100 social science experiments—entailing more than 1,000 hypothesis tests—that were selected by experts via a competitive process and fielded on probability samples of US adults between 2012 and 2020. Inclusion in the analysis is only conditional on the experiment qualifying for data collection, and not in any way on study results or publication. Results show that less than a third of proposed hypotheses were supported by the data, implying many more null findings than ostensibly appear in the published literature. We find that the largest predictor of positive experimental results was sample size. This is somewhat surprising, given that experimental studies typically take power considerations into account prior to data collection. In our data, the importance of sample size stemmed from small effect sizes across studies (perhaps smaller than researchers may have anticipated), highlighting a tension between commonly used power calculi and determining what constitutes a “meaningful effect.” We also find that moderation hypotheses were rarely significant, and that using multiple items for outcome measures did not affect results as expected. But indicators of research experience predicted higher rates of positive results, suggesting that there may be some room for optimizing experiment outcomes by minimizing design errors.
From Concurrent to Push-To-Web Mixed-Mode: Experimental Design Change in the German Social Cohesion Panel
Social Science Computer Review
Carina Cornesse, Julia Witton, Julian B. Axenfeld, Jean-Yves Gerlitz, Olaf Groh-Samberg
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Research shows that concurrent and sequential self-administered mixed-mode designs both have advantages and disadvantages in terms of panel survey recruitment and maintenance. Since concurrent mixed-mode designs usually achieve higher initial response rates at lower bias than sequential mixed-mode designs, the former may be ideal for panel recruitment. However, concurrent designs produced high share of paper respondents relative to web respondents. Since these paper respondents have been found to be at higher risk of attrition, cause higher data collection costs, and slow down the fieldwork process, sequential mixed-mode designs may be more practical in the regular course of the panel study after recruitment. Our study provides experimental evidence on the effect of switching a panel study from concurrent to sequential mixed-mode design after the panel recruitment. Results show that this switch significantly increases the share of online respondents without harming response rates. Respondents who are pushed to the web by the design change differ significantly from respondents who continue to participate via paper questionnaires with regard to a number of socio-digital inequality correlates. This suggests that, while the share of online respondents can be increased through mode sequencing, keeping the paper mail mode option is vital for ensuring continued representation of societal subgroups.
Gather Demographic Data About Gender, Sexuality, and Relational Identities: Asking the Right Questions
Advances in Methods and Practices in Psychological Science
Eleanor J. Junkins, Jaime Derringer
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In this tutorial, we suggest ways to improve current practices for measuring gender identity, sexual orientation, and demographics about relationships based on previous datasets and a newly collected survey of people’s behavior and perceptions of alternative-response formats. We apply lessons learned from racial identity/ethnicity to suggest broader principles of improving demographic measurement. We offer guides to meet the expectations of diverse stakeholders, including participants. The response options we recommend were curated to balance global identities and emerging trends to be applicable for online international research and in-person psychology research conducted primarily by U.S. institutions. We also offer practical suggestions for researchers to handle more complex data, including multiselect response options, which tend to be preferred by participants. Improved demographic data allow researchers to more fully capture multidimensional and complex social identities that are related to social inequities. In sum, the current tutorial is a guide to and discussion about challenges in collecting demographic data on social identities in which we use illustrative data to address important points related to measuring gender, sexuality, and relational demographics, specifically.
Thinking clearly about time-invariant confounders in cross-lagged panel models: A guide for choosing a statistical model from a causal inference perspective.
Psychological Methods
Kou Murayama, Thomas Gfrörer
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Yes stormtrooper, these are the droids you are looking for: Identifying and preliminarily evaluating bot and fraud detection strategies in online psychological research.
Psychological Methods
Thomas J. Shaw, Cory J. Cascalheira, Emily C. Helminen, Cal D. Brisbin, Skyler D. Jackson, Melissa Simone, Tami P. Sullivan, Abigail W. Batchelder, Jillian R. Scheer
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Simulating human well-being with large language models: Systematic validation and misestimation across 64,000 individuals from 64 countries
Proceedings of the National Academy of Sciences
Pat Pataranutaporn, Nattavudh Powdthavee, Chayapatr Archiwaranguprok, Pattie Maes
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Subjective well-being is central to economic, medical, and policy decision-making. We evaluate whether large language models (LLMs) can provide valid predictions of well-being across global populations. Using natural-language profiles from 64,000 individuals in 64 countries, we benchmark four leading LLMs against self-reports and statistical models. Unlike regressions, which estimate relationships from survey data, LLMs draw only on individual characteristics (e.g., sociodemographic, attitudinal, and psychological factors) together with associations encoded during pretraining, rather than from the survey’s subjective well-being responses. They produced plausible patterns consistent with known correlates such as income and health, but systematically underperformed relative to regressions and showed the largest errors in underrepresented countries, reflecting biases rooted in global digital and economic inequality. A preregistered experiment revealed that LLMs rely on surface-level linguistic associations rather than conceptual understanding, leading to predictable distortions in unfamiliar contexts. Injecting contextual information partly reduced—but did not remove—these biases. These findings demonstrate that while LLMs can simulate broad correlates of life satisfaction, they fail to capture its experiential and cultural depth. Accordingly, they should not be used as substitutes for human self-reports of well-being; doing so would risk reinforcing inequality and undermining human agency.
The importance of local racial demographic changes in democratic erosion in the mass American public
Proceedings of the National Academy of Sciences
Andrew Ifedapo Thompson, Stefan D. McCabe
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Violent sentiment is deeply tied to racial threat from the changing racial demography of the United States. Extending the historical idea of White flight, we find shifting local racial demographic conditions in tandem with a simple prime of national conditions causally drive more violent, antidemocratic attitudes across White Americans. We term this as “White fight sentiment.” Across four experiments conducted over the span of 3 y, using probability, state targeted, and convenience samples, we find that when we randomly prime national diversification among White Americans in locations that experienced local Black population increase or White decline, they become expressively, consistently more extreme when primed. Surprisingly, we consistently find null effects in communities that recently experienced Hispanic and Asian population change, short of one case across our four studies. Through a series of robustness checks we confirm national considerations specifically activate White fight.
Reranking partisan animosity in algorithmic social media feeds alters affective polarization
Science
Tiziano Piccardi, Martin Saveski, Chenyan Jia, Jeffrey Hancock, Jeanne L. Tsai, Michael S. Bernstein
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Today, social media platforms hold the sole power to study the effects of feed-ranking algorithms. We developed a platform-independent method that reranks participants’ feeds in real time and used this method to conduct a preregistered 10-day field experiment with 1256 participants on X during the 2024 US presidential campaign. Our experiment used a large language model to rerank posts that expressed antidemocratic attitudes and partisan animosity (AAPA). Decreasing or increasing AAPA exposure shifted out-party partisan animosity by more than 2 points on a 100-point feeling thermometer, with no detectable differences across party lines, providing causal evidence that exposure to AAPA content alters affective polarization. This work establishes a method to study feed algorithms without requiring platform cooperation, enabling independent evaluation of ranking interventions in naturalistic settings.