I checked 7 public opinion journals on Sunday, April 12, 2026 using the Crossref API. For the period April 05 to April 11, I found 9 new paper(s) in 3 journal(s).

Journal of Elections, Public Opinion and Parties

Being populist is bad for you: a six-wave longitudinal study on the relationships between populist orientation and perceived control
Michele Roccato, Silvia Russo
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Electoral outcomes versus voters' preferences: on the different tales the data can tell
Salvatore Barbaro, Anna-Sophie Kurella, Maike Roth
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Journal of Survey Statistics and Methodology

Effects of Interviewer Language and Dialect Choice on Questions About Political Trust: Examining the Asian Barometer Survey in China, the Philippines, and Indonesia
Mao Li, Victoria Owens, Fred Conrad
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This study explores how interview language affects measurement error in political trust assessments in multilingual countries, specifically China, the Philippines, and Indonesia. We propose a mechanism to explain how interview language shapes the cultural and cognitive frames respondents apply when formulating their answers, specifically evaluating its effect on trust-related survey questions. We hypothesize that interviewing multilingual respondents in their country’s official language, rather than their native language, triggers a cultural/cognitive frame that discourages the disclosure of negative opinions about political institutions. We studied China, the Philippines, and Indonesia using fourth-wave Asian Barometer Survey data, fitting a linear mixed-effects model with a matching procedure to predict trust in political institutions based on interview language. Our findings indicate that respondents in the Philippines, China, and Indonesia who were interviewed in the official language reported greater trust in political institutions than those interviewed in their native language. This phenomenon highlights the potential measurement error caused by interview language choice in cross-national and multilingual surveys, calling for greater attention from survey researchers.
Analysis of Risk and Protective Factor Surveillance for Noncommunicable Diseases Using A MultiMode Data Collection Approach
Laura Cordeiro Rodrigues, Izabella Paula Araújo Veiga, Letícia De Oliveira Cardoso, Rafael Moreira Claro
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Telephone surveys have faced challenges, including declining response rates and increasing costs, prompting the need for alternative data collection methods. Multimode data collection has emerged as a viable approach, producing high-quality data while reducing costs and improving response rates. This study evaluated the feasibility of a multimode data collection approach for the surveillance of risk and protective factors for noncommunicable diseases in Brazil, assessing its impact on response rates, costs, and data quality compared to a telephone only survey. In the multimode study individuals were invited via Short Message Service to participate in an online survey, and non-respondents, after reminders, were subsequently contacted by telephone. Data from the multimode study were compared with telephone-only interviews conducted using the Vigitel 2023 methodology. Design weights were applied to adjust for differential nonresponse, and final calibration weights aligned the sample’s sociodemographic composition with the target population through the raking method. The sociodemographic composition of the samples was compared. The prevalence of 23 health indicators was compared between the samples. Method effect was defined as the percentage variation in indicator prevalence between the multimode and telephone-only, reflecting differences attributable to data collection mode. Performance indicators, including eligibility rate, response and refusal rates, average interview cost, and interview duration, were also assessed. The multimode study showed sociodemographic similarity to the target population. Among 23 health indicators, only one differed between surveys (weighted comparison). Three indicators (passive smoking at home, e-cigarette use, and negative self-rated health) showed high method effect values, and one (obesity) was negatively associated with the multimode study (Prevalence Ratio: 0.68, 95 percent CI: 0.56–0.82). These findings indicate that multimode data collection is a viable option for the surveillance of risk and protective factors for noncommunicable diseases, yielding prevalence estimates comparable to those from telephone-only surveys, with greater operational speed and slightly lower cost.
Total Survey Error and the Potential Overestimation of Childhood Influenza Vaccination in the National Immunization Survey
Nicholas Davis, Tammy A Santibanez, James A Singleton, Katherine E Kahn, Yusheng Zhai
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The National Immunization Survey-Flu (NIS-Flu) monitors influenza vaccination among children in the United States, and the accuracy of NIS-Flu estimates is important for evaluating influenza vaccination programs. Total survey error (TSE) provides a framework for assessing survey accuracy. NIS-Flu data from the 2015–16 through 2017–18 influenza seasons were examined to assess components of nonsampling error: noncoverage of households by the sampling frame; household nonresponse; and measurement error resulting from parental reporting of vaccination status. We estimated the distributional parameters of each source of error from related surveys and auxiliary data and employed simulation to estimate bias. We estimated bias in end-of-season estimates of influenza vaccination rates and quantified the extent to which each source of survey error contributed to total bias. Overall point estimates (and 95 percent interval estimates) of total estimated bias were 8.0 (1.3, 14.6), 8.9 (2.6, 15.2), and 6.1 (−0.5, 12.8) percentage points for the 2015–16, 2016–17, and 2017–18 influenza seasons, respectively. Measurement error resulting from parental recall of children’s vaccination status was the largest contributor to bias; the average estimates of measurement error were 7.0, 8.2, and 5.5 percentage points for the three seasons, respectively. Errors due to noncoverage and nonresponse were relatively small (averaging <1 percentage point). Estimates of total bias were larger for Hispanic and non-Hispanic Black children and for the youngest children aged 6–23 months. Findings suggest NIS-Flu influenza vaccination rate estimates may be biased upward, primarily due to measurement error in the form of overreporting influenza vaccinations by parental respondents, with relatively little error due to noncoverage or nonresponse.

Social Science Computer Review

Emotional Communication Cost: The Impact of Emotional Polarization on the Effectiveness of Government Responses
Zheng Yang, Yiming Wei, Xi Lu
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Achieving online governance depends on the government’s effective response to public appeals through online political engagement. The effectiveness of the government’s response has been found to be influenced by multiple factors, including the textual characteristics of those public appeals. This article explores the impact of emotional bias and the polarization of citizens’ appeal messages on the effectiveness of government responses, through natural language processing and quantitative analysis methods of 1,553,572 public appeals on China’s Government Online Message Board on the People’s Daily website. The findings show a clear and consistent mechanism impacting the effectiveness of government response: the more polarized the emotion, the longer the time and the more words required for the government to respond, resulting in lower response efficiency. These results provide new insights for understanding contemporary digital governance, citizen digital political engagement, and online political consultation, specifically around the ‘emotional communication cost’ involved in government responses.
Crime and Calculation: The Decision-Making of Dark Web Actors
Ekaterina Botchkovar, Olena Antonaccio, Abigail Ballou, David Maimon
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Drawing on rational choice and social learning theories, this study examines how social networks, subcultural immersion, and specific activities shape dark web actors’ perceptions of risks and rewards. Using original 2024 survey data from 123 active dark web users recruited across English- and Russian-language forums and Telegram channels, we analyze how peer involvement, sustained participation in deviant subcultures, and interest in particular illicit activities influence perceived risks of detection and perceived benefits. Findings suggest that larger peer networks and deeper subcultural immersion may lower perceived risks and heighten perceived rewards. We also find important activity differences: interest in malware correlates with lower perceived risks, ransomware with higher perceived risks, and selling illicit goods with particularly high perceived rewards. These results underscore the fluid, socially constructed nature of risk and reward perceptions in clandestine spaces, offering rare empirical insight into the subjective mechanisms underlying cybercriminal choices and informing targeted prevention strategies.
Intelligent Artifice: Machine Learning From the Middle Ages to the Enlightenment
E. R. Truitt
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This introduction outlines the contributions of the four following essays on the subject of the long history of artificial intelligence. They address the longstanding links between artificial intelligence and deception, the liberatory potential that AI offers, and the way that humans have used automata and robots to test and assert the limits of humanity. Taken together, they reveal provocative and unexpected elements of continuity with contemporary discussions about artificial intelligence and machine learning.
“Leibniz, Computing, and AI”
Audrey Borowski
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Centuries before the advent of computers, the German philosopher and mathematician Gottfried Wilhelm von Leibniz (1646–1716) sketched out a “computational ontology” whereby information operates as an organic principle imposing order, molding and driving it, in such a way that the world gains a form of consciousness, and thought produces its being at the same time as it thinks itself.