I checked 7 public opinion journals on Thursday, July 23, 2026 using the Crossref API. For the period July 16 to July 22, I found 7 new paper(s) in 6 journal(s).

International Journal of Public Opinion Research

Impunity and coordination under polarization: public legitimacy and anti-corruption enforcement
Carlos Pereira, Mariana Furuguem, Frederico Bertholini
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The lack of coordination among accountability institutions is widely recognized as a driver of elite impunity in democratic systems. At the same time, enhanced coordination among prosecutors, judges, and enforcement agencies can raise concerns about due process and judicial impartiality. This article examines how political polarization shapes citizens' evaluations of institutional coordination in anti-corruption efforts. Using Brazil's Lava Jato operation as an empirically salient and ideologically charged context, we field a web-based survey experiment that assesses public support for a hypothetical legislative reform designed to increase coordination among accountability institutions while explicitly acknowledging its potential legal trade-offs. We show that citizens broadly support coordination even when informed of possible risks to defendants' rights. However, when coordination is explicitly associated with Lava Jato, ideological polarization structures these evaluations: right-wing respondents become more supportive of coordination, while left-wing respondents become more skeptical. We argue that polarization shifts the object of legitimacy from judicial outcomes to institutional design, transforming coordination itself into a contested political object. The findings identify a mechanism through which polarization constrains the public legitimacy—and, thus, the political feasibility—of institutional reforms aimed at combating corruption.

Journal of Elections, Public Opinion and Parties

Black and Latino American support for cross-ethnic coalitions: evidence from two conjoint experiments
Kenicia Wright, Güneş Murat Tezcür
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Affective polarization and electoral turnout: testing the moderating role of political sophistication on the Italian case
Antonino Castaldo, Danilo Di Mauro, Vincenzo Memoli
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Journal of Official Statistics

Strengthening Digital Survey Implementation for Official Statistics Using Text Mining: Evidence from Feedback Dataset of the Digital Domestic Tourism Survey 2024
Hanun Nabila Azis, Erna Nurmawati, Teguh Sugiyarto, Eko Rahmadian
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The shift toward non-traditional data sources has made Mobile Positioning Data (MPD) a key tool for more flexible and scalable data collection. By utilizing SMS-to-web invitations from network providers, this method improves coverage, timeliness, and cost efficiency, though it still faces hurdles regarding response rates, respondent burden, and respondent trust. This study analyzes respondent feedback from the Digital Domestic Tourist Survey 2024 using sentiment analysis and topic modeling. The most frequently discussed aspects were survey application reliability (64.48%), web questionnaire presentation (63.53%), perceived ease of use (63.09%), and questionnaire content (59.80%). Positive sentiment dominated all aspects, accounting for at least 61% of responses, indicating an overall favorable perception. Topic modeling of survey question variables produced a coherence score of 0.4199. Higher coherence was observed for the positive sentiment dataset (0.5447) compared to the negative sentiment dataset (0.4869), suggesting a well-structured alignment with the study’s framework. Despite the generally positive evaluation, improvements are needed in application reliability, questionnaire design, incentive clarity, data collection methods, and communication strategies to reduce respondent burden, and enhance participation in MPD-based SMS-to-web surveys.

Journal of Survey Statistics and Methodology

Using Opt-In Non-Probability Surveys to Estimate COVID-19 Infection and Vaccination Rates
Alexi Quintana-Mathé, Ata A Uslu, Jason Radford, James N Druckman, Kristin Lunz Trujillo, Alauna Safarpour, Katherine Ognyanova, Matthew A Baum, Jonathan Schulman, Roy H Perlis, Mauricio Santillana, David Lazer
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Public health crises demand timely surveillance of disease and interventions. This was a substantial challenge during COVID-19 in the United States due to the federalized response. States varied widely in infection and vaccination rates. Continuous state-level probability samples for tracking were unavailable and would have been logistically and financially onerous. Administrative data eventually became inaccurate. We thus evaluate the accuracy of large-scale opt-in non-probability state and national samples (from the Covid States Project) that estimated infection and vaccination rates on a near-continuous basis. The estimates aligned closely with a high-quality national probability sample and state-level administrative data (when such data were reliable). We offer evidence that the success of the surveys, compared to other less accurate non-probability surveys, may have stemmed from the successful recruitment of respondents with low trust in health institutions (i.e., individuals who often avoid surveys). We conclude by discussing how the Covid States Project can inform further data collection efforts requiring extensive spatial and temporal coverage.

Public Opinion Quarterly

Reevaluating News and Opinion Dynamics in the Iraq War: New Evidence for Social Identification Effects
Zachary Jablow, Scott L Althaus
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What causes changes in popular support for American wars? Competing theories posit that either the tone and content of wartime news or social identity cues conveyed through mass media should play the larger role. We offer new evidence in this debate by analyzing a novel set of rolling cross-sectional opinion data collected continuously over 13 months during an early phase of the Iraq War and pairing it with data on news intensity and the evaluative tone of news coverage during that same period. Contrary to conventional information updating explanations of war support but consistent with a social identification process, we find that greater intensity of wartime news coverage is associated with increases in aggregate support even after controlling for the evaluative tone of that news coverage.

Social Science Computer Review

Does Negativity Pay Off? The Impact of Political Party Attributes on the Use and Performance of Negative Campaigning in Digital Political Advertising
Hanna Paulke, Simon Kruschinski, Márton Bene, Jörg Haßler, Daniel Jackson, Darren Lilleker, Melanie Magin, Uta Russmann
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While research has shown how different political actors adapt engagement-triggering strategies in organic election campaigns on social media platforms, we know little about how such strategies are used in paid political advertising and how they affect algorithmic ad performance. To address this gap, this study analyzes how party attributes shape spending on, impressions of, and the cost efficiency of negative campaigning in digital political advertising. Manually content-analyzing all Facebook ads from 48 parties across 10 countries during the European Parliament election in 2019, we find that, on average, parties do not allocate more resources to negative ads, which also do not achieve higher impression counts and are even associated with higher costs per 1,000 impressions (cost efficiency). However, party characteristics matter: Whereas opposition parties invest more in negative campaigning and consequently gain more impressions than government parties, negativity only pays off in terms of cost efficiency for extreme parties. Our findings contribute to a better understanding of the interplay between advertiser characteristics and content strategies in shaping ad use and performance within commercial marketing infrastructure, emphasizing the need for greater transparency to ensure fair competition in digital political advertising.