I checked 7 public opinion journals on Sunday, April 05, 2026 using the Crossref API. For the period March 29 to April 04, I found 9 new paper(s) in 3 journal(s).

Journal of Elections, Public Opinion and Parties

Concurrent or not concurrent? Date selection of provincial elections in Argentina (1985–2023)
Andrés Lacher
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Suiting up or speaking out: analyzing candidate appearance & message complexity as heuristics for voter evaluation
Steven Perry, Matt Lamb
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Public Opinion Quarterly

Thinking Ideologically: The Limited Role of Left and Right Labels as Policy Shortcuts
Sarah Lachance, Clareta Treger
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How do voters use left-right ideological labels as shortcuts for policy positions in evaluating electoral candidates? We offer a distinction between maximal and minimal forms of ideological thinking. While maximal thinking implies that voters rely on ideological proximity as a proxy for policy congruence with candidates, minimal thinking requires only that voters use ideological labels to infer candidates’ positions—even if their own ideological identification is inconsistent with policy preferences. Drawing on original experimental data from Canada (N = 1,087)—a multiparty system with a fluid ideological landscape—we find that voters’ ideological self-placement is often misaligned with their policy positions, especially among right-leaning individuals. However, voters still use ideological proximity to infer candidates’ policy stances in the absence of policy information, supporting the Minimal Theory. These findings contribute to theories of political decision-making beyond the United States and have implications for substantive representation in systems with centrist or ideologically flexible parties.
United or Divided? A Polarized Society’s Response to War
Yuval Feinstein, Geffen Ben-David
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Recent global crises have renewed interest in the rally-’round-the-flag phenomenon of public opinion. At the same time, many studies have focused on deepening political polarization across countries. This study synthesizes these two lines of research by exploring how public opinion in a deeply polarized society responds to a security crisis that, in a less polarized context, would likely have led most citizens to close ranks behind a government that declared war on national enemies. We analyzed original panel data collected in Israel before and after the October 7 Hamas attack and during the subsequent Israeli military operation in Gaza. The findings reveal a split pattern: while the vast majority of Jewish Israelis supported the war and trusted the security forces, trust in the government and prime minister remained low. The analysis further identifies two distinct sets of mechanisms of attitude. Support for the war and trust in the security forces were associated with threat perceptions and anger about the enemy’s actions. In contrast, trust or mistrust in the government and prime minister hinged on whether respondents attributed blame for the crisis to the government or to the oppositional protest movement, an assessment tied to their preexisting views on the government’s controversial “judicial reform” initiative. These results suggest that extreme political polarization can prevent the emergence of a unified rally behind governments during severe security crises, mainly when internal strife produces contested views about the government’s responsibility for the crisis.
Perceived Economic Contributions Increase Positivity Toward Undocumented Immigrants
Marco M Aviña
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Undocumented immigrants contribute to the US economy by participating in the labor force, paying taxes, and starting businesses. They do so under constant fear of deportation and while being barred from government assistance programs. Nevertheless, misconceptions about how they affect the job market and public finance persist, exacerbating animus and hindering policy reforms. Across three survey experiments and three national samples of Americans, I assess two informational interventions to increase positivity toward this group: facts, which tackle misinformation, and narratives, which foster empathy. Both interventions yield positive results overall, with anecdotal accounts of “hardworking” undocumented immigrants proving most effective among those most negatively predisposed against them. The persuasive success of economic considerations in this domain has concrete implications for policymakers and advocates in their efforts to rally public support for immigration reform and against mass deportations. Further, these findings complicate motivated reasoning accounts and suggest that belief updating is possible, provided information is tailored to the intended audience.

Social Science Computer Review

How Much Data Should I Request? Balancing Richness and Compliance in Digital Trace Data Donations
Ernesto de LeĂłn, Laura Boeschoten, Fabio Votta, Joris Mulder, Bella Struminskaya, Daniel Oberski, Theo Araujo, Claes de Vreese
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Digital trace “data donation” studies offer researchers a unique opportunity to collect high-quality behavioral data, but decisions about the scope of requested data can impact both dataset richness and participant compliance. This paper examines the tradeoffs between requesting larger data packages, which include more extensive historical records, and participants’ willingness to donate. In a randomized experiment with Facebook and Instagram data donations, we compare a control condition where participants are asked to request the default 1-year data period to a treatment condition in which they are asked to request data for their entire account history. We analyze how different request sizes affect (1) participants’ compliance rates and (2) the characteristics of the data resulting from these different requests. We find that participants asked to request more data are less likely to complete the task. However, we propose that this is not primarily due to heightened privacy concerns, but rather because these data packages are significantly larger and therefore take longer for the platforms to deliver. This additional time to deliver data packages results in increased attrition. In terms of the effects on the data itself, we show that decisions about the time-span of the data impacts not only the volume of data requested, but also has implications for measurement validity, as the temporal window fundamentally redefines what key constructs represent, potentially transforming intended static indicators into narrow snapshots of recent behavior. We provide guidance for researchers navigating these decisions, considering both the benefits of richer longitudinal data and the risks of reduced participation.
Computational Evidence for the Two-Dimensional Structure of Social Evaluation: Pandemic-Era Insights From Americans’ Perceptions of Chinese and Japanese on Twitter
Xuanlong Qin, Tony Tam
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Social evaluation is fundamental to everyday interactions, yet our understanding has been constrained by fragmented theories and the lack of a scalable method for tracking group attitudes in real time. This paper resolves this methodological gap by introducing and validating a computational framework that empirically synthesizes three major theoretical models (Stereotype Content Model, Dual Perspective Model, and Semantic Differential) within a unified word embedding space. We demonstrate that social evaluation is structured by two core latent dimensions: Warmth-Communion-Evaluation (WCE), capturing affective and moral judgments, and Competence-Agency (CA), reflecting perceptions of ability and effectiveness. To validate its real-world utility, we apply this framework to U.S.-based Twitter posts about Chinese and Japanese individuals before and during the COVID-19 pandemic. Our analysis reveals that while perceptions of competence (CA) remained stable, affective evaluations (WCE) of Chinese individuals declined sharply, a dynamic not observed for Japanese individuals. This work offers a robust, scalable instrument for tracking intergroup attitudes during crises and provides a crucial bridge between social psychological theory and computational social science, enabling the real-time analysis of intergroup dynamics.
The Black Box, Animated Idols, and Racialization
Lamia Balafrej
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This essay argues that the black box—both as cryptic device and as critique of illegibility—is not unique to modern technology and has deep roots in the medieval Mediterranean world. Technical opacity was frequently addressed in Latin and Arabic sources, often with a critical undertone. Then as now, technoskeptical writers saw the self-acting device as treacherous, due to its reliance on hidden labor and mechanisms. This critique arose especially in relation to unfamiliar or foreign devices, like animated idols; as such, it was often racializing, attributing opacity as well as deceit to the object and its makers. Modern critiques of technology that focus on invisible labor may reproduce similar biases by enforcing a privileged, first-world perspective. A transhistorical approach thus not only shows the enduring history of the black box; it also illuminates the religious genealogy of techno-skepticism, as well as the biases that inhere in the black box, especially when deployed as a critical discourse.
Contagion Mechanisms and Emotional Group Polarization Outcomes of Online Toxicity: An Information Ecology Perspective
Han Luo, Xiao Meng
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Drawing on information ecology theory, this study investigates how online toxicity spreads and drives emotional group polarization in Reddit discussions surrounding the Israel–Palestine conflict. Based on a dataset comprising 8,725 posts and 1,628,366 comments, we employ Google’s Perspective API to detect toxic content, BERTopic to extract discussion topics, and a dictionary-based method to measure affective features. The results show that, from the information content perspective, content related to conflict and political topics is more prone to generating toxicity. From the information user perspective, post toxicity reduces the scale of user interaction while simultaneously increasing the level of comment toxicity. Furthermore, the analysis shows that post toxicity provokes comment toxicity by triggering users’ negative or high-arousal emotions, with discrete negative emotions such as anger, sadness, and fear enhancing the positive impact of post toxicity on comment toxicity. From the information environment perspective, the results indicate that post toxicity is not significantly associated with emotional group polarization. Accordingly, post toxicity alone plays a very limited role in explaining emotional group polarization in online discussions. These findings advance our understanding of toxicity dynamics in online environments and offer evidence-based strategies for moderators, platform designers, and policymakers to mitigate harmful discourse and foster healthier online communities.