Political Bias Research Articles

Do professors favor liberal students? Examining political orientation appearance cues and professor bias

The perception of political bias in higher education persists even in the face of scarce evidence that liberal professors penalize conservative students or favor liberal ones. We investigated the degree to which college professors used student appearance to ascertain political orientation, and whether liberal-looking students were rated more favorably. Ninety-eight (98) professors rated a student on logic, likeability, and political leaning. The hypothetical student’s dress (bohemian vs. business casual) and hairstyle (brown hair vs. pink hair) were manipulated to cue political orientation. Results indicated that professors used student appearance to ascertain liberal political leaning but did not rate the students significantly different on logic and likeability. These results suggest that while professors use appearance cues, they do not favor students who appear liberal leaning or punish those who look less liberal.

How to Define Sexual Health? A Qualitative Analysis of People’s Perceptions

Objectives Sexual health is an essential aspect of overall health that affects an individual’s physical, psychological, and social well-being. Understanding people’s perceptions of sexual health is essential because it can impact their sexual health-related behaviors, namely, their interactions with health services, campaigns, information, and policies. Furthermore, these perceptions may have a systemic impact, as public health policies related to promoting sexual health can be influenced by social factors. Such perceptions may also influence individuals’ sexual expression and interactions with sexual partners. Thus, an understanding of people’s perceptions of sexual health can facilitate the appropriate seeking of sexual healthcare, inform professional interactions with patients and the community, and guide policymakers in the promotion of it. Methods A total of 151 people living in Portugal, aged 19 to 75, answered a cross-sectional online questionnaire with an open-ended question: “In your opinion, what is sexual health?”. The data was analyzed using reflexive thematic analysis. Results We created four themes: (1) Let’s get physical, physical, (2) I’m in charge!, (3) I am not alone in this, and (4) Sexual justice is a must!. Participants presented diverse and complex views of sexual health, considering that it includes physical and biological components, cognitive and behavioral aspects and relational factors, and it is framed by the social and political context. Conclusions This study emphasizes that defining and achieving sexual health goes beyond healthism and needs to be considered at multiple levels. It highlights the need for individual awareness and self knowledge, to recognize equity within relationships and the strive for social equality and sexual rights. The study also emphasizes the significance of considering and respecting sexual developmental when promoting positive attitudes toward sex in formal and informal settings, increasing education about sexual pleasure, accepting and celebrating sexual and gender diversity, recognizing consensual non-monogamous relationships, and the need for inclusivity within sexually tolerant societies. Viewing sexual health through a political lens may play a crucial role in reshaping societal norms, promoting sexual justice, and influencing policymakers to better address and support the sexual health needs of a population following their own perspectives and expressed needs.

Comparative analysis of the image of a Chinese migrant in the Chinese mainland media and the media of Chinese emigration

The research presents a comparative analysis of the image of a Chinese migrant in the mainland Chinese media and the media of Chinese emigration. The research is based on the study of the content of publications such as The People's Daily and Xinhua on the one hand, and emigrant media, including The World Journal and The Epoch Times, on the other. The aim of the study is to identify differences and similarities in the representation of Chinese migrants, as well as to assess the influence of the political and cultural context on the formation of their image. In the Chinese mainland media, migrants are often presented as successful and patriotic representatives of the nation, keeping in touch with their homeland, which corresponds to China's "soft power" strategy. The expatriate opposition media is also biased in shaping the image of the Chinese migrant, often labeling migration as political rather than economic. The object of the study is the materials of the Chinese mainland and migrant media on the issues of Chinese emigration in the period 2023-2024. The subject of the study is the image of a Chinese migrant in the Chinese media. The methodology of this study includes content analysis and quantitative analysis of Chinese news media texts. As a result of the conducted research, the main similarities and significant differences in the representation of Chinese migrants in mainland Chinese media and emigrant media were revealed. The image of a migrant in the Chinese mainland media is formed within the framework of state propaganda, with an emphasis on patriotism and the preservation of cultural ties with the Motherland. Migrants are portrayed as successful representatives of the Chinese nation, keeping in touch with China and promoting its interests abroad. This reflects China's state policy of strengthening "soft power" and supporting the diaspora for economic and cultural influence in the international arena. The expatriate opposition media are also biased in shaping the image of the Chinese migrant, often labeling migration as political rather than economic. On the other hand, independent expatriate media such as the World Journal reflect more diverse and often critical points of view, highlighting the problems of migrant integration, discrimination and the complexities of life in another country. Independence from the Chinese authorities allows these media to focus on practical issues, avoiding political bias.

Extracting Political Interest Model from Interaction Data Based on Novel Word-level Bias Assignment

In democratic countries, political interest is deeply involved in people's daily lives. Research in political consumerism shows that product purchase decision is also influenced by the political orientation of the consumer. In traditional recommendation system design, user interest in an item is provided by a unified model. Recently, interest disentanglement methods have been introduced. It is shown that by disentangling interest factors such as conformity and private interest, recommendation performance can be significantly improved. However, few studies attempt to disentangle political interest in purchase behavior, which is bipolar. In this paper, we propose a method to extract political interest model from e-commerce interaction data, which is supported by a novel word-level political bias assignment. For the bias assignment part, we improved a political bias distilling method. For the political interest model extraction part, we extend a one-side bias method to make it support bipolar bias. We compare our method with state-of-the-art baseline methods in several evaluation settings, and the experimental results show that our method can achieve superior performance. Further investigation shows that our method is consistent with theories of political consumerism.

Liberal versus conservative distrust: A construal-level approach to dissimilarity in the workplace.

The dramatic rise in political polarization and aggravation of race relations are prominent in the United States. While dissimilarity to others is thought to undermine trust, I challenge the assumption that dissimilarity does so uniformly in the workplace where cross-party and cross-race interactions are structurally induced. Leveraging construal-level theory, I theorize that deep- versus surface-level differences with a coworker interact with ideology to activate higher versus lower construals of trustworthiness, prompting liberals and conservatives to distrust their coworkers in different ways. For liberals, I argue that perceived political dissimilarity undermines perceived person trustworthiness (a higher level/abstract construal, capturing one's trustworthiness generally as a person in the world) and disclosure. For conservatives, I argue that perceived racial dissimilarity undermines perceived role trustworthiness (a lower level/concrete construal, capturing one's trustworthiness specifically in their job) and reliance. Study 1 (a proof of concept) and Study 2 (a longitudinal, dyadic field study) utilize inductive theory-building and exploratory analyses. Studies 3a, 3b(i), and 3b(ii) (three preregistered experiments) support my hypotheses: Liberals tend to view politically dissimilar coworkers as less trustworthy people in the world and refrain from disclosures, while conservatives tend to view racial outgroup coworkers as less trustworthy in their jobs and refrain from reliance. Given liberal and conservative employees' roles in the calcification of political and racial group cleavages, respectively, organizations must determine whether both forms of bias should be addressed-indeed, racial bias is socially unacceptable, whereas political bias is widely tolerated-and, if so, whether interventions should target employees based on ideology. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The Role of Civil Society and Religious Organizations in Shaping Environmental Policy in Bangladesh

Research Problem: The intersection of religion, civil society, and public policy is an increasingly relevant area of study, particularly in the context of environmental degradation. In Bangladesh, the impacts of climate change, industrialization, and globalization have created significant environmental challenges. These challenges necessitate a critical examination of the role of civil society, including religious organizations, in addressing environmental issues. The key question is: How effectively is civil society, in conjunction with religious institutions, contributing to the environmental movement and influencing policy reform in Bangladesh? Research purposes: This paper aims to explore the role of civil society, including the influence of religious organizations, in the environmental movement in Bangladesh. It seeks to understand how civil society organizations engage in advocacy, lobbying, stakeholder pressure, environmental impact assessments, and grassroots mobilization. The goal is to evaluate how these efforts shape public policy on environmental governance in a religious and sociopolitical context. Research methods: : This study uses a qualitative, review-based approach, relying on secondary data from existing literature, media reports, and policy documents. It critically examines the involvement of civil society organizations in the environmental movement, with a focus on how religious values and institutions intersect with public policy efforts in Bangladesh’s environmental governance. Results and Discussion: The findings suggest that civil society organizations, including those with religious affiliations, play an important role in influencing environmental policy in Bangladesh. Through advocacy, lobbying, and public mobilization, these organizations have brought attention to critical environmental issues, facilitating public participation in environmental governance. However, challenges remain, including political biases and limited resources, which affect their ability to fully shape policy. Religious organizations have also been shown to contribute moral and ethical dimensions to environmental activism, aligning their values with sustainable development goals. Research Implications and Contributions: The research underscores the importance of integrating religious organizations into the broader framework of civil society engagement in environmental governance. It highlights how religious values can complement public policy efforts, contributing to a more holistic approach to sustainable development. The paper provides recommendations for policymakers to strengthen collaboration between civil society, religious institutions, and government bodies to make environmental policy more effective and inclusive, aligning with the journal’s scope of exploring the intersection of religion and public policy.

A Cross-Lingual Media Profiling Model for Detecting Factuality and Political Bias

Media profiling offers valuable insights to enhance the objectivity and reliability of news coverage by providing comprehensive analysis, but the diversity in languages posed significant challenges to our identification of factuality and political bias of non-English sources. The limitation of existing media analysis research is its concentration on a singular high-resource language, and it hardly extends to languages beyond English. To address this, we introduce xMP, a dataset for zero-shot cross-lingual media profiling tasks. xMP’s cross-lingual test set encompasses 34 non-English languages and 18 language families, extending media profiling beyond English resources and allowing us to assess cross-lingual media profiling model performance. Additionally, we propose a method, named R-KAT, to enhance the model’s zero-shot cross-lingual transfer learning capability by building virtual multilingual embedding. Our experiments illustrate that our method improves the transferability of models in cross-lingual media profiling tasks. Additionally, we further discuss the performance of our method for different target languages. Our dataset and code are publicly available.

The Contrasting Risk Communication Strategies of European Leaders during the COVID-19 Crisis

Abstract COVID-19 brought the role of leaders under intense scrutiny; their communication and framing of the crisis was crucial during the initial period of uncertainty. UK prime minister Boris Johnson and German chancellor Angela Merkel, managed and communicated the first wave of the crisis (March-June 2020) very differently. The clear contrast between pandemic response in two countries, with similar population sizes, wealth, and exposure to COVID-19, provides a lens through which to reflect on the different risk communication strategies utilized by both leaders. Following a grounded theory approach, the communication strategies of both leaders were examined. Transcripts from 31 press conferences from the initial announcement of COVID-19 to the end of the first wave were examined, and key themes identified. The analysis was framed using the CDC’s Crisis and Emergency Risk Communication lifecycle model, allowing for a structured comparison across different phases of the crisis. The findings were examined through the broader socio-political context of their communication. Similar themes were present in both leaders’ speeches, this included a focus on national identity; national strategy; health situation and social solidarity. However, they did so in markedly different ways. Merkel’s consistent, evidence-based communication strategy was more closely aligned with risk communication best practice compared to Johnson’s initial populist approach, which ultimately required a significant mid-crisis adjustment. Their different approaches also reflect their personas as political figures. Key messages • The consistent, science-based communication strategies exemplified by Merkel closely followed risk communication best practice and is likely enhanced public compliance and trust during the crisis. • These finding demonstrate the importance of incorporating a political lens to understand leaders approaches to risk communication and in public health research more broadly.

Political-RAG: using generative AI to extract political information from media content

ABSTRACT In the digital era, media content is crucial for political analysis, providing valuable insights through news articles, social media posts, speeches, and reports. Natural Language Processing (NLP) has transformed Political Information Extraction (IE), automating tasks such as event extraction and sentiment analysis. Traditional NLP methods, while effective, are often task-specific and require specialized expertise. In contrast, Large Language Models (LLMs) powered by Generative Artificial Intelligence (GenAI) offer a more integrated solution. However, domain-specific challenges persist, which led to the development of the Retrieval-Augmented Generation (RAG) framework. RAG enhances LLMs by incorporating external data retrieval, addressing issues related to data availability. To demonstrate RAG’s capabilities, we introduce the Political-RAG system, designed to extract political event information from media content, including Twitter data and news articles. Initially developed for event extraction, the Political-RAG system lays the foundation for developing various complex Political IE tasks. These include detecting hate speech, analyzing conflicts, assessing political bias, and evaluating social trends, sentiment, and opinions.

Political biases and inconsistencies in bilingual GPT models—the cases of the U.S. and China

The growing popularity of ChatGPT and other large language models (LLMs) has led to many studies investigating their susceptibility to mistakes and biases. However, most studies have focused on models trained exclusively on English texts. This is one of the first studies that investigates cross-language political biases and inconsistencies in LLMs, specifically GPT models. Using two languages, English and simplified Chinese, we asked GPT the same questions about political issues in the United States (U.S.) and China. We found that the bilingual models’ political knowledge and attitude were significantly more inconsistent regarding political issues in China than those in the U.S. The Chinese model was the least negative toward China’s problems, whereas the English model was the most critical of China. This disparity cannot be explained by GPT model robustness. Instead, it suggests that political factors such as censorship and geopolitical tensions may have influenced LLM performance. Moreover, both the Chinese and English models tended to be less critical of the issues of their “own country,” represented by the language used, than of the issues of “the other country.” This suggests that multilingual GPT models could develop an “in-group bias” based on their training language. We discuss the implications of our findings for information transmission in an increasingly divided world.

Closer to the people? Determinants of citizen–MP contact in Africa

AbstractIn this paper, we investigate the determinants of contact between citizens and Members of Parliament (MPs) in Africa by combining theories of contact developed in advanced Western democracies with theories of clientelism developed in the Global South. Based on Afrobarometer data matched with constituency‐level electoral data, we provide a first analysis of the determinants of citizen–MP contact in 32 African countries, encompassing a broad range of regime types. We find that smaller districts and single‐member districts strengthen contact across regime types, while electoral competitiveness is only positively associated with contact in more democratic settings. In line with clientelist theories of public resource access, district links to national ruling coalitions are positively associated with contact, but we find little evidence of partisan bias. Overall, we find that contact theories travel remarkably well across regions and regime types, and we caution against interpreting clientelistic contacts as harmful for democracy.

The role of artificial intelligence in higher medical education and the ethical challenges of its implementation

Artificial intelligence (AI) is penetrating higher medical education; however, its adoption remains low. A PRISMA-S search of the Web of Science database from 2020 to 2024, utilizing the search terms “artificial intelligence,” “medicine,” “education,” and “ethics,” reveals this trend. Four key areas of AI application in medical education are examined for their potential benefits: Educational support (such as personalized distance education), radiology (diagnostics), virtual reality (VR) (visualization and simulations), and generative text engines (GenText), such as ChatGPT (from the production of notes to syllabus design). However, significant ethical risks accompany AI adoption, and specific concerns are linked to each of these four areas. While AI is recognized as an important support tool in medical education, its slow integration hampers learning and diminishes student motivation, as evidenced by the challenges in implementing VR. In radiology, data-intensive training is hindered by poor connectivity, particularly affecting learners in developing countries. Ethical risks, such as bias in datasets (whether intentional or unintentional), need to be highlighted within educational programs. Students must be informed of the possible motivation behind the introduction of social and political bias in datasets, as well as the profit motive. Finally, the ethical risks accompanying the use of GenText are discussed, ranging from student reliance on instant text generation for assignments, which can hinder the development of critical thinking skills, to the potential danger of relying on AI-generated learning and treatment plans without sufficient human moderation.

Perceiving AI intervention does not compromise the persuasive effect of fact-checking

Efforts to scale up fact-checking through technology, such as artificial intelligence (AI), are increasingly being suggested and tested. This study examines whether previously observed effects of reading fact-checks remain constant when readers are aware of AI’s involvement in the fact-checking process. We conducted three online experiments ( N = 3,978), exposing participants to fact-checks identified as either human-generated or AI-assisted, simulating cases where AI fully generates the fact-check or automatically retrieves human fact-checks. Our findings indicate that the persuasive effect of fact-checking, specifically in increasing truth discernment, persists even among participants without a positive prior attitude toward AI. Additionally, in some cases, awareness of AI’s role reduced perceived political bias in fact-checks among Republicans. Finally, neither AI-generated nor human fact-checks significantly affected participants’ feelings toward or their perceptions of the competence of the targeted politicians.

Experience in applying large language models to analyse sociological data obtained as a result of interviews on students’ perception of entrepreneurial activity

Modern society is experiencing a digital transformation of various spheres associated with the development of artificial intelligence and big data. The introduction of large language models (hereinafter referred to as LLM) into scientific research opens new opportunities, but also raises a number of questions, which makes it relevant to study the peculiarities of their application for qualitative data analysis in sociology. The purpose of this article is to explore how LLM can influence the methodology and practice of sociological research, and to identify the advantages and disadvantages of their application. The authors rely on the use of the Calude-3 LLM to qualitatively analyse empirical data from a sociological study of students’ perception of ­entrepreneurship. The possibilities of LLM in the analysis of qualitative data are revealed: analysis of sentiment, construction of logical conclusions, classification, clustering, and formation of typologies. The advantages of using LLM are shown: increased data processing speed, saving time and resources. The application of LLM becomes a tool to optimise the research process in sociology, allowing to deepen the analysis of qualitative data, but it also has a number of limitations: social and political bias, difficulties with hallucinations. It is necessary to increase the transparency of models, improve their interpretability and explainability and reduce their social and political bias as well as ethical and legal regulation of the use of LLM models.

Political polarization and corruption: A theoretical and empirical review

Notwithstanding the considerable scholarly and public attention that political polarization and corruption have attracted in recent years and the important mechanisms through which the former may influence the latter, research in this area remains limited and inconclusive. This article offers a comprehensive theoretical and empirical synthesis of the current state of research in this domain. It finds that a large fraction of the apparent contradictions can be attributed to the conceptual inconsistencies and ambiguity surrounding political polarization. The types of polarization that have an inherently hostile and uncivil element (usually referred to as affective or pernicious polarization) undermine democratic accountability, which leads to more corruption. The role of ideological polarization among parties and the general population is more complex: it may boost accountability and decrease corruption but can also contribute to the aforementioned harmful forms of polarization and enhance the role of partisan bias in public opinion formation, thereby increasing corruption. The overall effect of ideological polarization on corruption may depend on the nature and the degree of the former, as well as on mitigating contextual factors. The two may create a vicious circle as corruption also increases political polarization via various channels.

How political consultants can leverage partisan media combativeness in the U.S.

ABSTRACT The growth of partisan media presents new challenges for political consultants. Informed by social identity theory and truth-default theory, this paper examines how U.S. voters react to politicians in combative news interviews. Experiment 1 (N = 320) establishes that an ingroup politician gains more trust among ingroup voters when interviewed by cross-partisan media accusing the politician of deception than when interviewed more congenially by co-partisan media. Experiment 2 (N = 131) finds that perceived media hostility increases Democrats’ and Republicans’ trust in a politician regardless of whether the interviewer accuses the politician of deception or is congenial. Experiment 3 (N = 126) replicates the findings when a Democrat is accused of deception on Fox News. The study tested a moderated mediation model, finding that Republican and Democratic voters do not react differently in the process. The discussion highlights the practical and theoretical implications of hostile media perceptions and ingroup–outgroup partisan bias in a polarized media environment with conflicting exposure to live fact-checking and deception detection.

Psychological underpinnings of partisan bias in tie formation on social media.

Individuals preferentially reciprocate connections with copartisans versus counter-partisans online. However, the mechanisms underlying this partisan bias remain unclear. Do individuals simply prefer viewing politically congenial content, or do they additionally prefer socially connecting with copartisans? Is this driven by preference for in-party ties or distaste for out-party ties? In a Twitter (now called X) field experiment, we created bot accounts varying by partisanship and whether they identified as bots or humans. We randomly assigned Twitter users (N = 3,013) to be followed by one of these accounts. We found evidence for social motivation-users were much more likely to reciprocate links to copartisan relative to counter-partisan accounts when the accounts identified as humans versus bots. We also found evidence for both in-party preference and out-party dispreference-users were as likely to follow back copartisan accounts as they were unlikely to followback counter-partisan accounts, compared to politically neutral accounts. A follow-up survey experiment (N = 990) provides further evidence for distinct roles of issue polarization, out-party animosity, and in-party affinity in moderating follow-back decisions online. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Translation of British Relations with China from an Explicitation Perspective (I)

British Relations with China is a political commentary taken from the Edinburgh Review(1802-1929). It delves into the political and commercial interactions between Britain and China in the mid-19th century and is marked by overt political bias and personal nuances. The study analyzes the English-to-Chinese translation of British Relations with China from the perspective of the Explicitation of Ideational Metafunction. Interpretation, addition, extension, conversion and substitution are employed to make metaphors, euphemistic expressions or omitted information explicit.

Supplemental Material for Psychological Underpinnings of Partisan Bias in Tie Formation on Social Media

Supplemental Material for Psychological Underpinnings of Partisan Bias in Tie Formation on Social Media

"News has various shades": Quantifying and Analyzing Media Bias at Aspect-level Granularity

This research presents a novel approach to dissecting media narratives, with a specific focus on aspect-level granularity and variance in addressing multifaceted news topics. Unlike previous studies, which often concentrate solely on ideological or political biases, our methodology delves deeper, exploring how diverse media outlets navigate the complexities of various news aspects. Through a detailed case study on Indian government policies, we uncover distinctive biases and variations in reporting between Indian and international media. Crucially, our methodology leverages Natural Language Inference (NLI) to identify news aspects and ascertain aspect-level sentiment from news text, enabling scalable and precise quantification of bias across diverse media narratives. Our findings illuminate the multifaceted layers of media coverage, revealing nuanced stances on different aspects of the same topic and the dynamic nature of biases over time. Importantly, our comprehensive framework quantifies media bias through data-driven quantitative evaluation, capturing both selection bias based on news aspect coverage and statement bias based on sentiment polarity. It is relevant to note that in our context, bias is not inherently favourable or unfavourable but rather serves as a quantitative metric to measure divergence in news presentation from the overall average. Thus, our contributions not only enhance understanding of media bias but also introduce a methodology distinguished for its comprehensive and scalable approach to analyzing media narratives, with substantial implications for future research and discussions in this domain.