I checked 7 public opinion journals on Wednesday, April 08, 2026 using the Crossref API. For the period April 01 to April 07, I found 4 new paper(s) in 2 journal(s).

Public Opinion Quarterly

United or Divided? A Polarized Society’s Response to War
Yuval Feinstein, Geffen Ben-David
Full text
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
Full text
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

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
Full text
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.
Contagion Mechanisms and Emotional Group Polarization Outcomes of Online Toxicity: An Information Ecology Perspective
Han Luo, Xiao Meng
Full text
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.