Political Leanings Research Articles

State Healthcare Regulations and Total Knee Arthroplasty Prices Across the United States.

State Healthcare Regulations and Total Knee Arthroplasty Prices Across the United States.

Automatic large-scale political bias detection of news outlets.

Political bias is an inescapable characteristic in news and media reporting, and understanding what political biases people are exposed to when interacting with online news is of crucial import. However, quantifying political bias is problematic. To systematically study the political biases of online news, much of previous research has used human-labelled databases. Yet, these databases tend to be costly, and cover only a few thousand instances at most. Additionally, despite the wide recognition that bias can be expressed in a multitude of ways, many have only examined narrow expressions of bias. For example, most have focused on biased wording in news articles, but ignore bias expressed when an outlet avoids reporting on certain topics or events. In this article, we introduce a data-driven approach that uses machine learning techniques to analyse multiple forms of bias, and that can estimate the political leaning of hundreds of thousands of Web domains with high accuracy. Crucially, this approach also allows us to provide detailed explanations for why a news outlet is assigned a particular political bias. Our work thereby presents a scalable and comprehensive approach to studying political bias in news on a larger scale than ever before.

Pictures from the primaries: Black presidential hopefuls and representation differences across the media bias and reliability spectrum

ABSTRACT This study explored bimodal news coverage of Kamala Harris and Cory Booker, the two leading Black candidates during the Democratic Primaries of the 2020 election season to set a point of comparison for how news media cover Black candidates. We analyzed emotional tone in images and headlines that appeared in coverage from online news platforms varying in political leanings and reliability. Results show that conservative-leaning outlets were more likely to lead news with negative headlines and emotionally expressive images of candidates than liberal-leaning media. Topics like political agendas and polling were more likely to be covered by lower-reliability organizations.

Integrated Assessment of Cost-Effective Water Quality Improvements in the Minnesota River Basin: Combining Stated Preferences and Simulation-Optimization Approaches.

Voluntary incentive programs are central to U.S. agricultural policy, aimed at enhancing sustainability by improving environmental outcomes and increasing the supply of non-market ecosystem services. This study integrates econometric insights with biophysical modeling to identify cost-effective strategies for nitrate and sediment reductions at the watershed scale. Survey data from Minnesota River Basin farmers characterizes willingness to accept (WTA) distributions for wetland restoration, cover crops, and nutrient management. A mixed logit model reveals significant heterogeneity in WTA, influenced by income, farm size, political leanings, taxes, water impairments, and non-pecuniary factors like ecosystem service appreciation, conservation experience, and stewardship. Integrated modeling highlights fluvial wetland restoration as a cost-effective and impactful strategy. Up to a 43% nitrogen reduction and 82% sediment reduction may be attained at an annual cost of under $10 million through targeted conservation investments. Scenarios with lower costs ($5 million annually) achieve substantial sediment reductions (82%) but limited nitrogen reductions (22%), demonstrating the utility of multi-objective optimization frameworks to elucidate optimal trade-offs in watershed planning.

The role of science in the climate change discussions on Reddit

Well-informed collective and individual action necessary to address climate change hinges on the public’s understanding of the relevant scientific findings. Social media has been a popular platform for the deliberation around climate change and the policies aimed at addressing it. Whether such deliberation is informed by scientific findings is an important step in gauging the public’s awareness of scientific resources and their latest findings. In this study, we examine the use of scientific sources in the course of 14 years of public deliberation around climate change on one of the largest social media platforms, Reddit. We find that only 4.0% of the links in the Reddit posts, and 6.5% in the comments, point to domains of scientific sources, although these rates have been increasing in the past decades. These links are dwarfed, however, by the citations of mass media, newspapers, and social media, the latter of which peaked especially during 2019–2020. Further, scientific sources are more likely to be posted by users who also post links to sources having central-left political leaning, and less so by those posting more polarized sources. Scientific sources are not often used in response to links to unreliable sources, instead, other such sources are likely to appear in their comments. This study provides the quantitative evidence of the dearth of scientific basis of the online public debate and puts it in the context of other, potentially unreliable, sources of information.

The role of place-based consciousness in COVID-19 vaccine hesitancy: A survey analysis across rural and urban subgroups in the U.S.

The role of place-based consciousness in COVID-19 vaccine hesitancy: A survey analysis across rural and urban subgroups in the U.S.

Who is Leading the Debate? Comparing Representations of the Public, Politicians and Experts in Newspaper Coverage of COVID-19 Policies in the UK.

This article presents a critical discourse analysis comparing linguistic representations of the public, experts, and politicians in UK newspaper reporting on COVID-19 policies. The analysis focuses on 120 articles published between 2020 and 2022, sourced from four national newspapers representing a cross-section of political leanings and formats. Quantitative and qualitative analyses of references and quotations suggest that the public is primarily represented as a collective entity, with functional references, rather than as distinct individual actors. Moreover, although the public is the most frequently mentioned among the groups considered, their engagement is mostly conveyed through emotional expressions of vulnerability, with little representation of individual voices. In contrast, politicians are depicted as individuals with far greater agency. Public health experts, meanwhile, are represented as having a marginal role in influencing policy decisions. The analysis of direct quotations carried in the media demonstrates that the stances expressed toward policies in such quotations consistently align with the ideological orientations of the newspapers across all three social groups. In newspapers with distinct left- or right-leaning perspectives, direct quotes tend to show greater levels of policy disagreement than in less ideologically polarised publications. Given that news discourse has been found to strongly influence public perceptions of public health policies, we suggest that the public might be better served by newspaper coverage of health crises that counters the trend of prioritising political biases over evidence-based conclusions. Moreover, featuring the perspectives of the public more prominently in such coverage might enhance positive policy engagement from some sections of the public.

Comparing large Language models and human annotators in latent content analysis of sentiment, political leaning, emotional intensity and sarcasm

In the era of rapid digital communication, vast amounts of textual data are generated daily, demanding efficient methods for latent content analysis to extract meaningful insights. Large Language Models (LLMs) offer potential for automating this process, yet comprehensive assessments comparing their performance to human annotators across multiple dimensions are lacking. This study evaluates the inter-rater reliability, consistency, and quality of seven state-of-the-art LLMs. These include variants of OpenAI’s GPT-4, Gemini, Llama-3.1-70B, and Mixtral 8 × 7B. Their performance is compared to human annotators in analyzing sentiment, political leaning, emotional intensity, and sarcasm detection. The study involved 33 human annotators and eight LLM variants assessing 100 curated textual items. This resulted in 3,300 human and 19,200 LLM annotations. LLM performance was also evaluated across three-time points to measure temporal consistency. The results reveal that both humans and most LLMs exhibit high inter-rater reliability in sentiment analysis and political leaning assessments, with LLMs demonstrating higher reliability than humans. In emotional intensity, LLMs displayed higher reliability compared to humans, though humans rated emotional intensity significantly higher. Both groups struggled with sarcasm detection, evidenced by low reliability. Most LLMs showed excellent temporal consistency across all dimensions, indicating stable performance over time. This research concludes that LLMs, especially GPT-4, can effectively replicate human analysis in sentiment and political leaning, although human expertise remains essential for emotional intensity interpretation. The findings demonstrate the potential of LLMs for consistent and high-quality performance in certain areas of latent content analysis.

Sovereign Spreads and the Political Leaning of Nations

ABSTRACTNations with a higher propensity to elect left governments tend to pay higher and more volatile sovereign spreads. We build a sovereign default model with elections between left and right policymakers. Reelection probabilities increase with government spending, with the left having a small advantage (consistent with the data). We use variation in “election efficiency” to create model economies that elect the left more (left leaning) or less frequently (right leaning) in equilibrium. The left‐leaning economy has a higher reluctance for fiscal austerity than the right‐leaning economy, chooses higher government spending, and faces higher spreads, resulting in lower welfare.

Marching Against a Rising and Manipulative Threat: Metaphorical Constructions of Populism in the Spanish and the Italian Press

Whereas the use of metaphors in populist political communication has been widely studied, few works have considered the way in which the concept of populism is constructed through metaphors in the public sphere and in the media. By applying Critical Metaphor Analysis (CMA) to a sample of newspaper articles published in Spain and Italy, we detect the main metaphorical frameworks used for discursively constructing populism in countries characterized by a polarized pluralist media system. Results show that populism is metaphorized in less than half of the analyzed items and that there are three common source domains for conceptualizing the term: path/travel/movement, conflict/war/crime and personification . While similar narratives can be drawn from the use of these source domains, different perspectives appear when looking at newspapers’ political leanings.

I’d hook up with them, but never date them: how attitudes towards hooking up influence willingness to date those with a criminal history

ABSTRACT While research suggests that marriage and relationships play an important part in desistance, there is a lack of research examining the role criminal stigma plays in creating romantic relationships and that attitudinal factors that may affect someone’s decision to pursue a relationship with formerly convicted individuals. The current study addresses this gap in the literature by examining the relationship between endorsement of hook up culture and willingness to date someone carrying a criminal history. Using street intercepts, over 600 adults in the United States were asked to complete a survey measuring various demographic and attitudes to examine their dating behavior. Results from the study suggest that a respondents’ endorsement of hook up culture influences the willingness of a person to engage in a committed relationship such as dating. Unsurprisingly, criminal history, crime type, political leanings, and gender also influenced the willingness to date someone with a prior conviction while controlling for other demographic factors. The results of the study implicate the importance of considering the attitudinal and contextual factors related to the decision to engage in romantic relationships, committed or otherwise, with people who have a criminal record.

Newspaper Favorites? A Comparative Assessment of Political Parallelism Across Two Decades

Newspapers in most West European countries have historically had strong ties to specific political parties. While formal bonds have vanished, parallelism in news content might still remain; for instance, in a tendency to report more often and more favorably on parties that align with the political leaning of a newspaper. In this article, we ask whether political parallelism exists in newspapers today, and whether or not it has decreased over the last two decades. These questions are answered using a dataset of 5.4 million newspaper articles from three countries (Denmark, the Netherlands, and the United Kingdom) over 20 years, annotated with the presence of political parties, and the sentiment of party news, at the sentence level. Findings suggest that newspapers pay more attention to the mainstream party with which they share political leaning, but that this pattern of parallelism has weakened over time.

The evolution of online news headlines

As the written word has moved online, new technological affordances and pressures – such as accelerated cycles of production and consumption – have changed how news headlines are produced and selected. Previous literature has linked certain strategies (e.g., clickbait) and linguistic features (e.g., length, negativity) to the success of text online (e.g., clicks). We tracked changes in the prevalence of those features in a sample of ca. 40 million news headlines across the last two decades from English-language outlets worldwide, focusing on the period in which the headline format adapted to the online context. We drew from a broad set of lexical, syntactic and semantic features from the literature to find the signature of the transition to online formats in the journalistic output of the last two decades. Many – but not all – of these features have become more prevalent over time, such as length and negativity. This systematic shift appeared across news outlets from different countries, political leanings, and of different journalistic quality. This may indicate an adaptation to the new affordances and pressures of the digital, online environment, and raises questions for the design of online environments in the future.

Bluesky: Network topology, polarization, and algorithmic curation.

Bluesky is a nascent "Twitter-like" and decentralized social media network with novel features and unprecedented data access. This paper provides a characterization of its interaction network, studying the political leaning, polarization, network structure, and algorithmic curation mechanisms of five million users. The dataset spans from the website's first release in February of 2023 to May of 2024. We investigate the replies, likes, reposts, and follows layers of the Bluesky network. We find that all networks are characterized by heavy-tailed distributions, high clustering, and short connection paths, similar to other larger social networks. BlueSky introduced feeds-algorithmic content recommenders created for and by users. We analyze all feeds and find that while a large number of custom feeds have been created, users' uptake of them appears to be limited. We analyze the hyperlinks shared by BlueSky's users and find no evidence of polarization in terms of the political leaning of the news sources they share. They share predominantly left-center news sources and little to no links associated with questionable news sources. In contrast to the homogeneous political ideology, we find significant issues-based divergence by studying opinions related to the Israel-Palestine conflict. Two clear homophilic clusters emerge: Pro-Palestinian voices outnumber pro-Israeli users, and the proportion has increased. We conclude by claiming that Bluesky-for all its novel features-is very similar in its network structure to existing and larger social media sites and provides unprecedented research opportunities for social scientists, network scientists, and political scientists alike.

Reducing Climate Change Denial and Increasing Support for Climate‐Friendly Policies: The Role of Climate Change Education

ABSTRACTInsufficient US public education and misinformation from other sources contribute to climate change (CC) denial. Public US university students in the South (Study 1) and Northeast (Studies 1 and 2) were randomly assigned to watch two educational science videos on CC (experimental condition) or flu viruses (control condition). Experimental (vs. control) condition participants reported (a) less agreement with statements reflecting CC denial (immediate post‐test [Studies 1 and 2] and delayed post‐test [Study 2]); (b) greater agreement with statements about the existence, seriousness, and human causes of CC and hope for CC interventions (immediate post‐test [Studies 1 and 2]); (c) greater intentions to support climate‐friendly US policies (immediate post‐test [Study 1]); and (d) less negative feelings about CC (delayed post‐test [Study 2]), when controlling for gender and political leaning. Implications for effectively addressing CC education among university students with relatively easy‐to‐implement, time‐efficient, and cost‐effective interventions are discussed.

Acceptance, perceptions, and compliance for COVID-19 vaccines among students attending a rural university: An interventional study using brief video messages

Objective: The purpose of this study was to examine the factors associated with vaccine compliance and the effectiveness of short-term video interventions on COVID-19 vaccine perceptions among students attending a state university located in rural Texas. Participants: A total of 298 students participated in an online survey. Methods: Students completed the COVID-19 Vaccine Acceptance Scale (COVID-VAC) and Perceptions of Vaccines Scale before and after watching one of three videos (neutral, educational, or disease effects). Results: Differences in vaccination status were observed for ethnicity and political leanings (p < 0.05). The video interventions did not impact COVID-VAC or Perceptions of Vaccines scores over time (p > 0.05). Conclusions: Short-term video interventions were ineffective in altering vaccine perceptions and improving acceptance of the COVID-19 vaccine in our study population. Impact of the type and duration of educational videos should be explored by future studies to combat vaccine hesitancy in future population-based studies.

A Narrative Persuasion Approach to Promoting COVID-19- Related Policy Support

Communication scholars warn against focusing on individual behaviors when discussing health issues, arguing that doing so can reduce affect and policy support. Although COVID-19 outcomes are linked to structural barriers to treatment, policy interventions appear to improve outcomes for vulnerable groups. Thus, strategic messages must promote public understanding of social determinants and policy support related to COVID-19. Using concepts from attribution theory and narrative persuasion, we employed an experiment (N = 435) testing the effects of personal responsibility (high, moderate, and low) on affective engagement and COVID-19 policy support. Namely, the manuscript examines (a) affective responses to characters displaying varying levels of personal responsibility for COVID-19 prevention, (b) the impact of these affective responses on policy support, and (c) the moderating role of audience political ideology on these effects. Analyses revealed that a highly responsible protagonist elicited empathy and perceived similarity, increasing policy support. While participants’ political ideology moderated protagonist responsibility on perceived similarity, a more responsible protagonist evoked empathy independently of political leaning. Theoretical and practical implications are offered.

Impact of Political Ideologies on Civic Engagement in South Korea

Purpose: The aim of the study was to analyze the impact of political ideologies on civic engagement in South Korea. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Political ideologies significantly influence civic engagement in South Korea, where citizens' political leanings often shape their participation in social and political activities. Conservative ideologies are typically associated with formal engagement, such as voting and policy advocacy, while progressive ideologies are linked to grassroots movements and activism on social issues. A key finding is that South Koreans with strong ideological identities are more likely to participate in civic activities, as these beliefs often align with specific causes or political agendas. Furthermore, generational divides play a role; younger progressives tend to engage in digital activism, while older conservatives favor traditional forms of participation. Unique Contribution to Theory, Practice and Policy: Civic voluntarism model, social identity theory &amp; theory of planned behavior may be used to anchor future studies on the impact of political ideologies on civic engagement in South Korea. To foster greater civic engagement, practical steps should be taken to encourage participation in ideologically diverse groups. Policymakers should consider reforming electoral systems to ensure that they reflect the diversity of political ideologies within a society.

Officer-Involved: The Media Language of Police Killings

Abstract This article examines language patterns in U.S. television news coverage of police killings. First, we document that the media use syntactic structures—such as passive voice, nominalizations, and intransitive verbs—that obscure responsibility more often in cases of police killings than in cases of civilian killings. Through an online experiment, we demonstrate the significance of these syntactic differences, revealing that participants are less likely to hold police officers morally responsible and demand penalties when exposed to obfuscatory language, particularly in cases involving unarmed victims. Further analysis of news data shows greater use of obfuscatory language when the victims are unarmed or video footage is available—situations in which obfuscation may have the greatest impact. Exploring the causes of this differential obfuscation, we do not find evidence that it is driven by either demand-side factors or supply-side factors associated with TV station ownership and political leaning. Instead, our results suggest that narratives crafted by police departments are more likely drivers of media obfuscation. This article highlights how syntactic choices and their semantic consequences in media shape perceptions, extending beyond coverage volume and bias.

Contextual predictors of belongingness in military and veteran students on university campuses

Objective: Prior research demonstrated that military/veteran students report lower belongingness than civilian students, but the reasons why remain unclear. We investigated the impact of demographic characteristics, state and local politics, and school-specific veteran resources on reported belongingness. Participants: Participants included 104,162 students (2,814 military/veteran) who completed a survey for the Healthy Minds Study between 2014 and 2018. Methods: A combined mixed effect model and models stratified by military status to determine differences in belongingness between military/veteran students and civilian students. Results: Unadjusted models indicated military/veteran students reported lower belongingness than civilian students (b = −0.10, p < . 001). However, adjusting for demographic characteristics and state and school attributes reduced this effect (b = −0.04, p = .001). Conclusion: We were able to demonstrate that military/veteran students’ reduced belongingness is largely due to the demographic differences among military/veteran students rather than aspects of the school or political leanings.