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!

Navigating Ambiguities: A Systematic Review and Comparative Analysis of Social Bot Detection Methods in Communication Research
Communication Methods and Measures
Xiao Meng, Xiaohui Wang, Tai-Quan Peng
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Psychological reactance theory and politeness theory: A test of competing explanations for the role of threat to freedom in conveying persuasive resistance
Communication Monographs
Christopher J. Carpenter, Adam Richards, Jie Zhuang
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Campaigning across platforms: how party status, social profiles, and emotional tone shaped user engagement with French MPs during the 2022 presidential election
Journal of Information Technology & Politics
Julien Figeac, Marie Neihouser, Jérémie Garrigues
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Unveiling ideological extremes in parliamentary debates using transformer-based language models
Journal of Information Technology & Politics
Barbara Kos, Lana Tuković, Ema Vlainić, Marina Bagić Babac
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Intrafamilial political discordance impacts familial and psychological well-being through reduced positive communication
Journal of Social and Personal Relationships
Branda Yee-Man Yu, Christian S. Chan
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Political disagreements within families can undermine both individual and relational well-being. This study analyzed varying configurations of parent-child political discordance—including partisan-partisan and partisan-neutral dyads—in Hong Kong ( N = 586) following the 2019 social unrest and examined its familial and psychological consequences over two weeks ( n = 200). Findings indicate that neutral-partisan dyads, similar to their partisan-counterparts, exhibited significantly larger differences in support for government, police, and anti-government protestors compared to politically concordant dyads. Dyads in which one member supported the anti-government (“ yellow ”) camp and the other supported the pro-government (“ blue ”) camp or identified as neutral reported lower levels of positive communication and poorer family functioning than dyads sharing the same stance. Mediation analyses revealed that reduced positive communication explained the impact of political discordance on increased psychological distress across discordant dyads. However, this mediation effect on family functioning was observed only in yellow - neutral and yellow - blue dyads. By incorporating partisan-neutral disagreements into the analysis, this study offers an ecologically valid account of parent-child political discordance among partisan and neutral family members, highlighting the potential threat to both personal and family well-being when intrafamilial communication is compromised.
Public Affairs News and Local Relevance in Digital Journalism: Comparing Nonprofit versus Commercial Digital News Outlets Across Levels of Community Pluralism
Journalism & Mass Communication Quarterly
Hsin-Han Lee, Wilson Lowrey
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Drawing from both critical political economy and community structure perspectives, this study compares local news quality in stories from nonprofit and commercial news sites in both high- and low- pluralism communities in the United States. Findings indicate that nonprofit business models offer benefits for news quality in local communities. Findings also show that these benefits from nonprofits are heightened in highly pluralistic communities (larger cities), though digital outlets overall showed signs of higher quality in less pluralistic cities. This research contributes to our understanding of the interplay between media business models, communities’ institutional structures, and local news content, particularly for digital news.
Audiovisual Fiction to Reduce Prejudices Against Non-Binary People
Media Psychology
Isabel RodrĂ­guez-de-Dios, Vitor Blanco-FernĂĄndez, MarĂ­a T. Soto-Sanfiel
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Reaching a larger audience: Content-related strategies of the far right on VK
New Media & Society
Veronika Borovinski
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The recent global rise of far-right ideologies has been accompanied by the normalization of these ideas in online communication. However, little is known about the strategies employed by the far right to drive this trend, particularly outside Western countries and major platforms. This study addresses these gaps by conducting a systematic content analysis of far-right content on VK (VKontakte), the most widely used Russian social network, to examine the content’s characteristics that facilitate the mainstreaming of the far right. Findings indicate that far-right actors leverage agenda-setting mechanisms and adopt news-like formats to embed xenophobic and exclusionary narratives within the broader mainstream Russian discourse. This study contributes to research on far-right content-related strategies and the interplay between non-Western contexts, digital affordances, and far-right communication in less regulated online spaces.
A Credible Change: How Parties Use Election Promises to Counteract The Loss of Reputation When They Dilute Their Policy Positions
Political Communication
Mathias Bukh Vestergaard
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What Kind of Depolarization Should We Aim For? Making Communication Transformative
Political Communication
Michael BrĂŒggemann, Christel W. van Eck, Shota Gelovani, Hendrik Meyer, Ashley Muddiman, Louisa Pröschel, Hartmut Wessler
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How Social Media Metrics Shape News Production: A Replication Study
The International Journal of Press/Politics
Rongxin Ouyang, Subhayan Mukerjee, Tian Yang
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Audience engagement signals on social media platforms have shaped how media outlets produce news. Mukerjee et al. examined this phenomenon empirically by estimating the extent to which media outlets respond to audience engagement signals on Facebook in deciding what news to publish on the platform. However, the extent to which their findings can be generalized to other social media platforms remains unknown. We replicate their study on Twitter using the same methodological pipeline ( N ≈ 4 . 55 million posts, twenty-eight media outlets, between 2015 and 2019). Our results indicate that media responsiveness to audience engagement on Twitter aligns with the core patterns identified in the Facebook study. Specifically, topics receiving higher audience engagement generally experience significantly increased coverage shortly thereafter, and the responsiveness is not conditioned on the nature of topics. However, we observe three differences in dynamics on Twitter compared to Facebook: first, the maximum response window on Twitter is shorter; second, conservative outlets on Twitter are not more likely to respond to engagement signals; third, platform-specific metrics (e.g., retweets) show different patterns of responsiveness. Our replication thus highlights the generalizability of the original study while underscoring the importance of platform-specific characteristics in shaping media production on social media.
More than Symbols: The Effect of Symbolic Policies on Climate Policy Support
American Political Science Review
THEODORE TALLENT, MALO JAN, LUIS SATTELMAYER
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As climate change effects become increasingly salient, the need for stringent climate policies becomes more pressing. The implementation of such policies is often met with resistance from the public due to their perceived costs and distributional implications. Scholars have mostly focused on material compensations to increase public support among policy losers. This article goes beyond the existing literature by showing how what we term symbolic policies can enhance support for costlier policies. We define symbolic policies as policies sending meaningful messages to the public but having low material impacts. We argue that without changing the material costs that climate policies impose, symbolic policies increase public support by altering the message that costly policies convey. We demonstrate our argument using survey experiments and qualitative interviews conducted in France, showing that symbolic policies can significantly increase support for costly climate policies and increase perceptions of fairness, elite behavior, and government credibility.
Leaking season: An analysis of the timing of media disclosures from party insiders in Sweden 2010-2024
Party Politics
Andreas BÄgenholm, Stephen Dawson, Birgitta Niklasson, Jenny De Fine Licht, Elsa Höök
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Why is compromising information about misconduct in political parties leaked to the media by party insiders? Drawing on previous research and interviews with political and investigative journalists, we hypothesize that such media disclosures are made with political intent and thus more likely when (1) party list nominations take place and (2) when parties are losing popular support. Through an analysis of 349 newspaper articles of misconduct in political parties leaked by party insiders to Swedish print media between 2010 and 2024, we find support for both expectations. We therefore conclude that intra-party leaks are indeed likely to be made with political intent, at least indirectly. This paper contributes novel theoretical and empirical insights to research on political parties, political scandals, and leaks and whistleblowing by illustrating the role media disclosures made by party insiders play in internal party power struggles.
Reassessing Extremism, Polarization, and Constraint with Continuous Policy Questions
Political Behavior
Anthony Fowler
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Some argue that the American public is extreme and polarized along party lines. Paradoxically, others argue that members of the public lack meaningful policy preferences and exhibit low constraint across issues. These conclusions are typically drawn from binary policy questions or scales with ambiguous values, both of which are ill-suited for measuring extremism, polarization, or constraint. In this paper, I reassess these claims by analyzing policy questions that allow respondents to express their preferences on a well-defined continuum. Across a wide range of issues, most Americans appear to have moderate preferences over policy. As expected, Democrats tend to be more liberal than Republicans, but there is significant overlap on every issue, and the average extent of disagreement is modest. Lastly, positions across issues appear more constrained than standard tests suggest.
Improving studies of sensitive topics using prior evidence: an informative Bayesian approach for list experiments
Political Science Research and Methods
Xiao Lu, Richard TraunmĂŒller
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Estimates of sensitive questions from list experiments are often much less precise than desired. We address this well-known inefficiency problem by presenting an informative Bayesian approach that combines indirect measures with prior information. Specifying informed priors amounts to a principled combination of information that increases the efficiency of model estimates. This framework generalizes a range of different modeling approaches for list experiments, such as the inclusion of direct items, auxiliary information, the double list experiment, and the combination of list experiments with other indirect questioning techniques. As we demonstrate in real-world examples from political science, the informative Bayesian approach not only improves the utility but also changes the substantive implications drawn from list experiments.
Navigating the mismeasurement of intermediary variables in message-based experiments
Political Science Research and Methods
Thomas Leavitt, Viviana Rivera-Burgos
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Researchers frequently deliver treatments through messages, as in many audit and get-out-the-vote (GOTV) experiments. These message-based experiments often hinge on intermediary variables—actions subjects must take to actually receive the treatment or control embedded in a message. Whether subjects open the message is a crucial intermediary step, which can serve as a condition for estimating downstream treatment effects or as an outcome of interest in its own right. Yet opens are often measured with error, most notably when some openers are misclassified as non-openers in email-based studies. We characterize the resulting bias, derive interpretable bounds on effects for well-defined subgroups, and provide sensitivity analyses for mismeasurement, thereby offering practical guidance for message-based experiments conducted through email and other communication technologies.
Holding Justice Accountable: Intensive vs. Extensive Margins in Prosecutor Elections
Public Opinion Quarterly
Dvir Yogev
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American public opinion has shifted away from tough-on-crime policies, yet the conditions for supporting progressive reform on the ballot remain unclear. This study develops a theory of voting behavior in prosecutor elections. I utilized the recall of a progressive prosecutor to examine voters’ revealed preferences in a pivotal crime and justice politics setting. I show that the correct response to voters requires attention to legal reform’s intensive and extensive margins. Despite the media narratives, I argue that voters favor reforming the intensity of the criminal legal system; voters support reducing outcomes’ harshness but not limiting the scope of prosecuted behavior. This research also indicates that moral concerns drive support for decreasing the intensive margin, while opposition to changing the extensive margin is rooted in the desire to maintain deterrence. Politicians who intend to end mass incarceration should focus on reducing the criminal legal system’s intensive margin to gain political approval.
Capability, Opportunity, and Motivation in a Social Multiplayer Online Game: Player Influence Dynamics in Sky: Children of Light
Social Science Computer Review
Wen Zeng, Chandni Kumar, Sinong Zhou, Donggyu Kim, Aimei Yang, Dmitri Williams
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This study investigates networked social influence in Sky: Children of the Light , a social multiplayer online game. Drawing on survey responses ( n = 9,254) and in-game data from over 660,000 players, we use an innovative graph-based machine learning approach to quantify how individuals influence others’ playtime, and regression analyses to test predictors from the COM-B model. Results show that Capability enhances influence, although excessive task focus correlates negatively with social impact; Opportunity emerges as the strongest predictor, with active social interactions significantly boosting influence; and Motivation varies by playstyle, with socializers and competitors demonstrating greater influence than narrative-focused players. By applying the COM-B model in a digital gaming context, this research highlights behavioral dimensions of player influence and employs a novel metric for quantifying interpersonal influence. These findings suggest practical implications for game design, particularly by highlighting how social interaction opportunities and different player motivations shape influence within communities.
Using large language models to estimate belief strength in reasoning
Behavior Research Methods
Jérémie Beucler, Zoe Purcell, Lucie Charles, Wim De Neys
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Brain Responses to Deepfakes and Real Videos of Emotional Facial Expressions Reveal Detection Without Awareness
Computers in Human Behavior
Casey Becker, Russell Conduit, Philippe A. Chouinard, Robin Laycock
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Evaluating Human-Based and Large Language Model-Based Content Analysis: A Case Study on Negative Word-of-Mouth Classification in Social Media
Computers in Human Behavior
Yolande Yang, Chih-Chien Wang, Pau-Lin Chou, Chieh-Yu Tien, Jia-Ci Wen, Nien-Hsin Chen
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Time-Varying Path-Specific Direct and Indirect Effects: A Novel Approach to Examine Dynamic Behavioral Processes with Application to Smoking Cessation
Multivariate Behavioral Research
Yajnaseni Chakraborti, Recai M. Yucel, Megan E. Piper, Jeremy Mennis, Anthony J. Alberg, Timothy B. Baker, Donna L. Coffman
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Changing Norms Following the 2024 U.S. Presidential Election: The Trump Effect on Prejudice Redux
Personality and Social Psychology Bulletin
Samuel E. Arnold, Jenniffer Wong Chavez, Kelly S. Swanson, Christian S. Crandall
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Following the 2016 U.S. Presidential election of Donald Trump, prejudice toward groups targeted during his campaign (e.g., Asian Americans, Mexicans) become more acceptable. By contrast, both Trump and Clinton voters reported less prejudice of their own. We conducted a 2024 conceptual replication, measuring perceived norms of prejudice and own-prejudice toward 128 groups, both before ( N = 362) and after ( N = 261) the U.S. election. We separately measured the negativity of Trump’s campaign rhetoric toward these groups ( N = 188). Levels of prejudice and perceived norms of prejudice acceptability were mostly stable pre-/post-election, but Trump’s negative rhetoric predicted an increase in perceived acceptability of prejudice among targeted groups (replicating the 2016 results), and a rise in self-reported prejudice in the same groups post-election (reversing the 2016 results). Despite changes in the sociopolitical context between elections, the election of a leading politician who campaigned on prejudice was again associated with increases in the acceptability of prejudice.
Time and Climate Change: U.S. Media Representations of Climate Actions, Horizons, and Events (2000 to 2021)
American Sociological Review
Oscar Stuhler, Iddo Tavory, Robin Wagner-Pacifici
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Questions of temporality are at the heart of climate change discourse: Does one think of climate change primarily as an event happening in the present, or as something that will take place in the future? By when must we take action to prevent its worst consequences? This article presents the first large-scale assessment of the structure and evolution of temporalities expressed in U.S. media discussions on climate change (2000 to 2021). To do so, we developed a novel computational framework for detecting and interpreting temporal expressions in textual data. Our analyses yield three main findings: First, temporal horizons for climate change have continuously shrunk since 2000, stably targeting, on average, the year 2060. However, second, while anticipated effects are getting closer, horizons for the coordination of climate action have remained highly stable, averaging around 16 years into the future at any given time. Third, contrasting the stability of explicitly stated horizons, we find a sharply expanding discourse of urgency patterned by outbursts of urgency: sudden surges in calls for immediate action or warnings against climate change’s devastating consequences during events like the 2020 California wildfires. By uncovering this disjuncture of different forms of temporality, we illuminate a crucial aspect of the climate change debate, contribute to the sociological theory of events, and identify some of the conditions underlying climate inaction.
Quantifying racial disparities in media representations of gun violence at scale
Proceedings of the National Academy of Sciences
Ruth Bagley, Susan Burtner, Andrew V. Papachristos, Rob Voigt
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Previous research has documented racial disparities in gun violence news coverage in limited and small-scale contexts. This study curates and analyzes a large-scale dataset of news articles linked to specific incidents of gun violence to test for systematic race-related differences in representation across the US news media. Using computational techniques, we quantify how much media attention an incident gets, the topics and linguistic style of articles, and how participants in the incidents are framed. We find significant generalized disparities in media coverage and portrayal of incidents depending on whether they occur in neighborhoods that are majority white or majority people of color (POC), including increased media attention on police shootings if they occur in majority POC neighborhoods, greater focus on the people involved in incidents in majority white neighborhoods, and increased racialization and framing related to crime in majority POC neighborhoods.