I checked 7 public opinion journals on Thursday, July 09, 2026 using the Crossref API. For the period July 02 to July 08, I found 11 new paper(s) in 4 journal(s).

International Journal of Public Opinion Research

The effects of personality traits in interview time length in cellphone public opinion surveys
Ridvan Peshkopia, Don Salihu
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The rapid proliferation of mobile phone opinion surveys calls for a better understanding of their efficiency. We explain the length of mobile phone survey interviews with respondent and interviewer personality traits from the Big Five personality model. Our results show that Agreeableness (which motivates harmony seeking) and Conscientiousness (which motivates duty fulfillment) were the best predictive traits, predicting shorter and longer interview times, respectively, when they characterized both the respondent and the interviewer. Neuroticism (which motivates threat sensitivity), however, predicted opposite effects. The two other personality traits of the Big Five model, Extraversion (which motivates social engagement) and Openness (which motivates novelty exploration) did not show significant effects. Moreover, we argue that while these core psychological traits are important separately, we should pay even more attention to their interaction. Our results show that the effects of the interactions are more complex than expected and require both careful interpretation and additional research. Our findings have practical implications for the public opinion survey industry, as they could help in the training of interviewers by taking into account their personality traits. We analyze data from a public opinion survey conducted in Albania and Kosovo during the winter of 2018–2019.

Journal of Elections, Public Opinion and Parties

Such a question, such an answer? An experimental study of wording effects in opinion surveys using the Swedish abortion law as a case
Henrik Friberg-Fernros, Elina Lindgren, Nora Theorin
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Implementing the mail ballot: gauging voter preferences using a discrete choice experiment
Dominic Nyhuis, Felix MĂĽnchow
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Misinformation and threats to self-interest
Mathieu Turgeon, Alessandro Freire
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COVID-19 and performance voting: evidence from the 2021 state assembly elections in India
Subhasish Ray, Holli A. Semetko, Kiran Arabaghatta Basavaraj, Pahi Saikia, Anil M. Varughese
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Public Opinion Quarterly

Welfare State Deservingness in the Era of Mass Higher Education
Sebastian Diessner, Niccolo Durazzi, Federico Filetti, David Hope, Hanna Kleider, Julian Limberg, Simone Tonelli
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The educational composition of labor markets has changed dramatically in recent decades. In many advanced democracies, the majority of workers now possess a university education. We currently know very little about how this transformation has influenced perceptions of welfare state deservingness, which are closely linked to support for the welfare state. This article addresses that gap in the literature by carrying out an original survey with a sample of 3,916 respondents from the United States. The survey combines a conjoint experiment with an information provision experiment. We find causal evidence that people are less inclined to provide welfare state assistance to the university educated than the non-university educated. This is primarily driven by need-based considerations: The university educated are seen as less in need of support, due to their strong labor market position in contemporary knowledge economies.
Ignoring Gender Compromises the Comparability of Cross-Cultural Survey Research
Andrej Findor, Kristína Kironská, Roman Hlatky, Ondrej Buchel, Matej Hruška, Amy H Liu
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Survey measures of intergroup attitudes may not necessarily be comparable across countries. Androcentric bias—the propensity to position men as the universal standard—is more likely to arise among speakers of grammatically gendered languages than among speakers of languages without grammatical gender. When combined with outgroup male target bias—the tendency to evaluate outgroup men more negatively than outgroup women—androcentric bias may distort cross-national comparisons of survey measures across different language types. To evaluate, we conducted survey experiments with over 19,500 participants from 13 European countries. We randomly assigned participants to evaluate: (a) masculine or gender-neutral outgroup labels, or (b) gender-inclusive alternatives. On average, gender-inclusive labels evoked more favorable evaluations. Importantly, these positive effects were more consistently present in grammatically gendered languages. Our findings highlight potential challenges to measurement validity posed by variations in the grammatical embedding of gender across languages. Using gender-inclusive language improves measurement and may serve as a first step toward bolstering cross-national comparability.
Christian Nationalism as a Social Identity
Brooklyn Walker, Paul A Djupe, Anand E Sokhey, Donald P Haider-Markel
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Over the past decade, research on Christian nationalism in the United States has grown substantially. Some of the associated public opinion literature has described Christian nationalism as an identity, and some of it as a worldview, but scholars have not grappled with this ambiguity or its consequences. Accordingly, we make two moves to bring conceptual order to this rapidly expanding literature. First, we use well-established social identity measures to assess whether respondents think of Christian nationalism as an identity, and we compare the responses to popular measures of the Christian nationalist worldview. Second, we use multiple survey experiments to evaluate the extent to which identification with Christian nationalism is dependent on the definition of Christian nationalism. We conclude that Christian nationalist identities exist, they are strongly linked with a Christian nationalist worldview, and to some extent they depend on the definition of the identity group. In this unique case of elite contestation of an emerging identity, we find that the typical worldview measure also serves effectively as a strength-of-identity measure.
Partisan Differences in Support for Political Violence: Results from a Natural Experiment in the United States
Chiara Vargiu, Alessandro Nai
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The polarized reaction to the assassination of the UnitedHealthcare CEO in December 2024 underscored the potential of ideologically framed acts of violence to undermine societal cohesion and challenge democratic norms. While many condemned the killing as an unjustifiable attack on a private citizen, others celebrated Mangione as a “folk hero,” glorifying him and his act as a symbol of resistance against an industry perceived as corrupt and dehumanizing. Using data from a rolling cross-sectional survey in the United States, we causally tested partisan differences in support for political violence before and after the CEO’s assassination and the perpetrator’s subsequent arrest. While Democrats initially condemned violence against Republicans, their support for partisan violence increased following Mangione’s arrest. These results underscore the role of public discourse in shaping attitudes toward political violence, raising concerns about the normalization of politically motivated aggression, even among groups traditionally less inclined to endorse it.

Social Science Computer Review

Automating Content Analysis With Multiple LLM Agents: Impacts of Agent Attributes and Human–AI Collaboration
Xinyan Zhao, Chengshuai Zhao, Mordecai Mengesteab, Chau-Wai Wong, Mengqi Zhan, Zhen Tan, Tianlong Chen
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Emerging research in computational social science has applied LLMs to automate content analysis, often by prompting a single model to act as a human coder. While a single LLM may suffice for a few manifest variables, it still falls short on diverse latent constructs. And the impact of LLM agent attributes on measurement outcomes remains unclear, limiting their validity for communication research. Drawing upon the literature on interacting agents and communication, this study examines the impact of agent diversity, agent open-mindedness, and human–AI collaboration (HAIC) in a multi-LLM-agent system for automated content analysis. The results demonstrate reliable and accurate measurement of four communication variables across three datasets, with improved performance following agent discussion. Additionally, agent open-mindedness, but not agent diversity, significantly affects measurement outcomes. These results highlight the potential of multi-LLM-agent systems for automated content analysis and suggest the importance of considering agent attributes and values in system design.
Modular Polyvocality: Community Detection and Semantic Analysis of Civil Society Discourse in English-Language #MahsaAmini Twitter Networks
Hossein Masoudnia, Alireza Samiee Esfahani, Mohsen Forghani, Mohammad Moghimi, Hossein Samiei Esfahany
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This study investigates how English-language Twitter discourse surrounding the #MahsaAmini protests (October 2022–February 2023) organized into distinct yet interconnected thematic communities within civil society networks. Combining Louvain community detection, sentiment profiling (via VADER), and semantic validation (Jensen–Shannon Divergence, MANOVA, cosine similarity), we map five protest “streams” reflecting modular issue alignments, from Documentation of events involving violence and On-the-Ground Mobilization to Monarchist Advocacy & Diaspora Political Engagement and Anti-IRGC Campaigns. While these communities differ in topical focus, their shared affective tone and overlapping lexicons point to modular polyvocality, a discourse structure characterized by thematic differentiation within broader rhetorical and affective coherence. This pattern represents polyvocal consensus rather than fragmentation. We interpret these findings through the lens of connective action, networked publics, and digital diaspora activism, arguing that the discourse reflects a transnational, modular, and affectively aligned subset of protest-oriented civil society mobilization within constrained information environments. This work contributes to debates on hybrid dissent, algorithmic visibility, and the structure of protest discourse in controlled digital contexts.