Hasil untuk "Political Science"

Christian Sparta

Adib Sakhawat, Tahsin Islam, Takia Farhin et al.

As large language models (LLMs) are increasingly deployed, understanding how they express political positioning is important for evaluating alignment and downstream effects. We audit 26 contemporary LLMs using three political psychometric inventories (Political Compass, SapplyValues, 8Values) and a news bias labeling task. To test robustness, inventories are administered across multiple semantic prompt variants and analyzed with a two-way ANOVA separating model and prompt effects. Most models cluster in a similar ideological region, with 96.3% located in the Libertarian-Left quadrant of the Political Compass, and model identity explaining most variance across prompt variants ($η^2 > 0.90$). Cross-instrument comparisons suggest that the Political Compass social axis aligns more strongly with cultural progressivism than authority-related measures ($r=-0.64$). We observe differences between open-weight and closed-source models and asymmetric performance in detecting extreme political bias in downstream classification. Regression analysis finds that psychometric ideological positioning does not significantly predict classification errors, providing no evidence of a statistically significant relationship between conversational ideological identity and task-level behavior. These findings suggest that single-axis evaluations are insufficient and that multidimensional auditing frameworks are important to characterize alignment behavior in deployed LLMs. Our code and data are publicly available at https://github.com/sakhadib/PolAlignLLM.

Arman Engin Sucu, Yixiang Zhou, Mario A. Nascimento et al.

This study investigates the use of Large Language Models (LLMs) for political stance detection in informal online discourse, where language is often sarcastic, ambiguous, and context-dependent. We explore whether providing contextual information, specifically user profile summaries derived from historical posts, can improve classification accuracy. Using a real-world political forum dataset, we generate structured profiles that summarize users' ideological leaning, recurring topics, and linguistic patterns. We evaluate seven state-of-the-art LLMs across baseline and context-enriched setups through a comprehensive cross-model evaluation. Our findings show that contextual prompts significantly boost accuracy, with improvements ranging from +17.5\% to +38.5\%, achieving up to 74\% accuracy that surpasses previous approaches. We also analyze how profile size and post selection strategies affect performance, showing that strategically chosen political content yields better results than larger, randomly selected contexts. These findings underscore the value of incorporating user-level context to enhance LLM performance in nuanced political classification tasks.

Nicole Smith-Vaniz, Harper Lyon, Lorraine Steigner et al.

Large Language Models (LLMs) have become increasingly incorporated into everyday life for many internet users, taking on significant roles as advice givers in the domains of medicine, personal relationships, and even legal matters. The importance of these roles raise questions about how and what responses LLMs make in difficult political and moral domains, especially questions about possible biases. To quantify the nature of potential biases in LLMs, various works have applied Moral Foundations Theory (MFT), a framework that categorizes human moral reasoning into five dimensions: Harm, Fairness, Ingroup Loyalty, Authority, and Purity. Previous research has used the MFT to measure differences in human participants along political, national, and cultural lines. While there has been some analysis of the responses of LLM with respect to political stance in role-playing scenarios, no work so far has directly assessed the moral leanings in the LLM responses, nor have they connected LLM outputs with robust human data. In this paper we analyze the distinctions between LLM MFT responses and existing human research directly, investigating whether commonly available LLM responses demonstrate ideological leanings: either through their inherent responses, straightforward representations of political ideologies, or when responding from the perspectives of constructed human personas. We assess whether LLMs inherently generate responses that align more closely with one political ideology over another, and additionally examine how accurately LLMs can represent ideological perspectives through both explicit prompting and demographic-based role-playing. By systematically analyzing LLM behavior across these conditions and experiments, our study provides insight into the extent of political and demographic dependency in AI-generated responses.

Sadia Kamal, Lalu Prasad Yadav Prakash, S M Rafiuddin et al.

The Political Compass Test (PCT) and similar surveys are commonly used to assess political bias in auto-regressive LLMs. Our rigorous statistical experiments show that while changes to standard generation parameters have minimal effect on PCT scores, prompt phrasing and fine-tuning individually and together can significantly influence results. Interestingly, fine-tuning on politically rich vs. neutral datasets does not lead to different shifts in scores. We also generalize these findings to a similar popular test called 8 Values. Humans do not change their responses to questions when prompted differently (``answer this question'' vs ``state your opinion''), or after exposure to politically neutral text, such as mathematical formulae. But the fact that the models do so raises concerns about the validity of these tests for measuring model bias, and paves the way for deeper exploration into how political and social views are encoded in LLMs.

John Pyrik

On November 15, 2023, Mr. John Pyrik presented the opening address for this year’s West Coast Security Conference. The key points discussed were the introduction of speakers for the international perspectives panel of the CASIS conference and their contribution to the field of intelligence.  Received: 01-04-2024 Revised: 01-26-2024

Lily Hamourtziadou

Ho-Chun Herbert Chang, Benjamin Shaman, Yung-chun Chen et al.

Visual content on social media has become increasingly influential in shaping political discourse and civic engagement. Using a dataset of 239,526 Instagram images, deep learning, and LLM-based workflows, we examine the impact of different content types on user engagement during the 2024 US presidential Elections, with a focus on synthetic visuals. Results show while synthetic content may not increase engagement alone, it mediates how political information is created through highly effective, often absurd, political memes. We define the notion of generative memesis, where memes are no longer shared person-to-person but mediated by AI through customized, generated images. We also find partisan divergences: Democrats use AI for in-group support whereas Republicans use it for out-group attacks. Non-traditional, left-leaning outlets are the primary creators of political memes; emphasis on different topics largely follows issue ownership.

Joseba Fernandez de Landa, Arkaitz Zubiaga, Rodrigo Agerri

Political leaning can be defined as the inclination of an individual towards certain political orientations that align with their personal beliefs. Political leaning inference has traditionally been framed as a binary classification problem, namely, to distinguish between left vs. right or conservative vs liberal. Furthermore, although some recent work considers political leaning inference in a multi-party multi-region framework, their study is limited to the application of social interaction data. In order to address these shortcomings, in this study we propose Hybrid Text-Interaction Modeling (HTIM), a framework that enables hybrid modeling fusioning text and interactions from Social Media to accurately identify the political leaning of users in a multi-party multi-region framework. Access to textual and interaction-based data not only allows us to compare these data sources but also avoids reliance on specific data types. We show that, while state-of-the-art text-based representations on their own are not able to improve over interaction-based representations, a combination of text-based and interaction-based modeling using HTIM considerably improves the performance across the three regions, an improvement that is more prominent when we focus on the most challenging cases involving users who are less engaged in politics.

Emma Johanna Puranen, Emily Finer, Christiane Helling et al.

Interest in science fiction's (SF's) potential science communication use is hindered by concerns about SF misrepresenting science. This study addresses these concerns by asking how SF media reflects scientific findings in exoplanet science. A database of SF exoplanets was analysed using a Bayesian network to find interconnected interactions between planetary characterisation features and literary data. Results reveal SF exoplanets designed after the discovery of real exoplanets are less Earth-like, providing statistical evidence that SF incorporates rapidly-evolving science. Understanding SF's portrayal of science is crucial for its potential use in science communication.

Scheilla Aprilia Murnidayanti, Titi Muswati Putranti

MSMEs are a growing and vital sector for the country's economy. However, until now, MSMEs taxpayer compliance is still low. DGT then digitized tax administration with the aim of reducing taxpayer compliance costs for MSMEs taxpayers. This paper analyzes the effectiveness of digitizing tax administration in reducing MSMEs taxpayer compliance costs and DGT's steps to reduce MSMEs taxpayer compliance costs. The method used in this study is qualitative with a literature study approach. Secondary data was obtained from various library sources, including books, encyclopedias, dictionaries, journals, documents, magazines, etc. The study results show that the digitization of tax administration in Indonesia has not reduced the cost of taxpayer compliance for MSMEs taxpayers. In addition, other factors that can influence MSMEs taxpayer compliance include knowledge, mediation, perceptions of fairness, and so on. DGT has simplified the tax system and digitized tax administration to reduce tax compliance costs. The originality of this research is in analyzing the relationship between the digitization of tax administration and tax compliance costs for MSMEs.

Indra Kusumawardhana, Gustin Saptarani Dewi

The Timor Gap had been a hotspot of territorial dispute between Australia and Timor-Leste. In 2018, Australia finally agreed to settle a permanent maritime boundary in favour of Timor-Leste. Why was Australia willing to sacrifice the border and give a favourable outcome to Timor-Leste? The research examined the importance of the tripartite approach to Foreign Policy analysis to understand why a country may choose seemingly unfavourable options in territorial disputes. The analysis showed how Australian foreign policy was influenced by agency-structure interactions within the international system. The research demonstrated that structural constraints at the international level influenced Australia’s decision, including the South China Sea dispute between ASEAN members and China, previous agreements Australia-Timor-Leste on the management of the Timor Gap, and domestic political dynamics in Australia. The research reveals a relationship between actors’ structural and dispositional dimensions in foreign policy. In the case of Australia, there is a strong link between democratic values ​​and respect for the international rules-based order. Altogether, this situation prompted Australia to continue negotiations with Timor-Leste over the Timor Gap and ultimately to accept an agreement for maritime delimitation in Timor-Leste’s favor.

Gaël Le Mens, Aina Gallego

We use instruction-tuned Large Language Models (LLMs) like GPT-4, Llama 3, MiXtral, or Aya to position political texts within policy and ideological spaces. We ask an LLM where a tweet or a sentence of a political text stands on the focal dimension and take the average of the LLM responses to position political actors such as US Senators, or longer texts such as UK party manifestos or EU policy speeches given in 10 different languages. The correlations between the position estimates obtained with the best LLMs and benchmarks based on text coding by experts, crowdworkers, or roll call votes exceed .90. This approach is generally more accurate than the positions obtained with supervised classifiers trained on large amounts of research data. Using instruction-tuned LLMs to position texts in policy and ideological spaces is fast, cost-efficient, reliable, and reproducible (in the case of open LLMs) even if the texts are short and written in different languages. We conclude with cautionary notes about the need for empirical validation.

WU Hongli, XUE Yunzhen, WU Junying

ObjectiveTo understand the research status quo and hotspots of the elderly migrant following child in China.MethodsThe relevant literature on the elderly migrant following child was retrieved from the China National Knowledge Infrastructure（CNKI） from 2010 to 2020，and the Citespace5.6.R5 bibliometric software was used for visual analysis.ResultsA total of 388 papers were included，and the number of published papers showed an overall upward trend；the source of disciplines was mainly sociology and supplemented by political science； qualitative research was the main method used in the field；author cooperation and institutional cooperation were loose；the research hotspots revolve around social integration，social adaptation，social support，elderly care in different places，influencing factors，and social work.ConclusionsThe publication level，research depth，and attention of the research literature on the elderly migrant following child need to be strengthened；research disciplines and methods need to be more abundant and diversified；cooperation need to deepen cross⁃unit，cross⁃regional，and cross⁃disciplinary collaboration；community care workers should pay more attention to the spiritual care of the elderly migrant following child，the government should also increase the purchase of social services.

Jaehyuk Choi, Lei Lu, Heungju Park et al.

This paper examines the effect of the political network of Chinese municipal leaders on the pricing of municipal corporate bonds. Using municipal leaders' working experience to measure the political network, we find that this network reduces the bond issuance yield spreads by improving the credit ratings of the issuer, the local government financing vehicle. The relationship between political networks and issuance yield spreads is strengthened in areas where financial markets and legal systems are less developed.

Mandeep Singh Rai

The subject of international institutions and power politics continues to occupy a central position in the field of International Relations and to the world politics. It revolves around key questions on how rising states, regional powers and small states leverage international institutions for achieving social, political, economic gains for themselves. Taking into account one of the rising powers China and the role of international institutions in the contemporary international politics, this paper aims to demonstrate, how in pursuit of power politics, various states (Small, Regional and Great powers) utilise international institutions by making them adapt to the new power realities critical to world politics.

E. Turnhout

This essay offers a critical engagement with the ideal of policy relevant environmental knowledge. Using examples in environmental governance and conservation, it argues that by packaging knowledge in terms and categories that are considered politically salient, scientists do not just inform policy-making by providing information about presumed pre-existing objects in nature and environment; rather, science is constitutive of those objects and renders them amenable for policy and governance. These political implications of scientific knowledge imply a need for critical scrutiny of the interests that science serves and fails to serve as well as mechanisms to ensure the accountability of science. This essay is a modified and expanded version of the inaugural lecture with the same title that was delivered on June 2, 2016 at Wageningen University, the Netherlands.

Frank R. Baumgartner, Beth L. Leech

A generation ago, scholars saw interest groups as the single most important element in the American political system. Today, political scientists are more likely to see groups as a marginal influence compared to institutions such as Congress, the presidency, and the judiciary. Frank Baumgartner and Beth Leech show that scholars have veered from one extreme to another not because of changes in the political system, but because of changes in political science. They review hundreds of books and articles about interest groups from the 1940s to today; examine the methodological and conceptual problems that have beset the field; and suggest research strategies to return interest-group studies to a position of greater relevance. The authors begin by explaining how the group approach to politics became dominant forty years ago in reaction to the constitutional-legal approach that preceded it. They show how it fell into decline in the 1970s as scholars ignored the impact of groups on government to focus on more quantifiable but narrower subjects, such as collective-action dilemmas and the dynamics of recruitment. As a result, despite intense research activity, we still know very little about how groups influence day-to-day governing. Baumgartner and Leech argue that scholars need to develop a more coherent set of research questions, focus on large-scale studies, and pay more attention to the context of group behavior. Their book will give new impetus and direction to a field that has been in the academic wilderness too long.

Pavlo Artymyshyn, Taras Polovyi

Продвижение идей „русского мира” – центральный элемент идеологического влияния России в Беларуси. В результате нарративы, призванные продвигать эту концепцию, активно распространяются в белорусском информационном пространстве. Целенаправленное информационное воздействие осуществляется через сеть пророссийских интернет-ресурсов с использованием характерного набора тезисов, приемов и формулировок, обосновывающих общую историю, национальное, языковое родство и необходимость объединения белорусского и русского народов. Подобные тезисы имеют место в контексте белорусской академической гуманитарной науки, которая часто, следуя советской традиции, идеологически служит политическим лозунгам современных пророссийских (в том числе проправительственных) кругов в Беларуси посредством своеобразной интерпретации исторических фактов и их адаптации к современным общественно-политическим процессам. Конечная цель исследуемых информационных сообщений – навязать белорусскому обществу идею об безальтернативности пророссийского вектора развития внешней политики Республики Беларусь и отрицать факт русификации белорусов.

Richard Holmes