Hasil untuk "Political theory"

Eric Msughter Aondover, Ifedolapo Ademosu, Ramson Oloche Acheme

The 2023 general elections in Nigeria were characterised by a surge in hate speech, particularly across digital platforms, significantly shaping the political landscape and influencing voter behaviour. The study highlights how ethno-religious and politically motivated hate speech deepened societal divisions, fostered misinformation, and contributed to voter apathy and fear-driven electoral choices. On social media platforms, individuals and organisations believe that freedom of speech entitles them to speak their minds without any restrictions whatsoever. During elections, this freedom of expression plays out without any hindrance, pervading social media platforms with hate speech rhetoric, misinformation, and disinformation. This study examines how voters’ exposure to political hate speech during the 2023 presidential election campaigns, as disseminated through traditional media, social platforms, and campaign rhetoric, shaped the attitude of voters, their trust in the ability of the candidates to deliver, and their level of electoral participation. Using the Functional Theory of Campaign Discourse, the study analyses the system through which inflammatory language divides public opinion, reinforces divisions in political party groups (among supporters), and destroys the confidence voters have in the Nigerian electoral processes. Based on the pragmatic approach of research design, survey method, and content analysis of hate speech in the 2023 presidential election campaigns will be adopted, and results show pervasive use of hate speech by the political class and how this results in low voter turnout.

Zoltan Bartha

This paper investigates the extent of political rent seeking in Hungary in the 2010s. Political capitalism--where powerful private interests influence public policy for private gain--creates opportunities for rent seeking that vary across sectors. The analysis is based on a theoretical model assuming rent seeking occurs in a three-stage process: changes in economic institutions granting regulatory privileges, which are enhanced by political-business networks; this leads to scarcities, and increased market power in certain markets; which then generates rents. To quantify this, the study evaluates Hungarian political capitalism by examining the impact of political decisions on firms' rents, analysing the profit trends of the 1,000 largest Hungarian firms (selected annually by net sales) and comparing their mean profit share (earnings before tax) across two periods: 2008-2012 and 2019-2023. A significant increase in a sector's mean profit share was assumed to indicate increased rent seeking. Using Welch's two-sample t-tests, three sectors were identified as potentially experiencing increased rent seeking: agriculture, construction, and financial and insurance activities. Quantitative findings include a 320% increase in mean agricultural profit share (70% in mean ROA), a more than fivefold increase in construction mean profit share (mean ROA from 3.3% to 10.1%), and a more than 6.5 times increase in financial sector mean profit share. Furthermore, a similar Czech analysis showed no significant increases in any sector's profit share, suggesting that the detected rises in Hungarian sectors are linked to domestic activities rather than external factors, which strengthens the findings.

Leena Badran, Niveen Rizkalla, Steven P. Segal

Abstract Background Existing evidence indicates that Muslim minorities underutilize mental health services despite a pressing need. Employing the Theory of Planned Behavior (TPB), this study seeks to explore considerations that influence mental health help-seeking by Muslims residing in California and Israel. Methods A qualitative approach involving semi-structured interviews guided by the TPB principles was implemented with 78 Muslim participants. Thematic analysis was conducted to identify key themes. Results Employing both deductive and inductive approaches, four major themes were identified: attitudes (advantages, disadvantages, and the influence of religiosity), subjective norms (the impact of significant others), perceived behavioral control (facilitators and challenges), and intentions toward seeking mental health support (influenced by gender, and prior experience). Common social and cultural norms were identified in both groups within the patterns of the TPB. The family's significance as a supportive resource emerged in both groups, but the extended family had a more profound impact among Muslims in Israel. Stigma as a barrier against seeking mental health help was stronger among Muslims in Israel, while financial barriers and socio-political context were highlighted more by Californian Muslims. Conclusions The findings highlighted the importance of adopting a holistic approach to mental health help-seeking among Muslims due to commonalities in approaches, irrespective of geographical differences. Variance between the two groups primarily stemmed from social factors, particularly stigma and the influence of extended family. The results underscore the universality of common aspects and emphasize the importance of addressing social norms and socio-economic realities to enhance engagement among Muslims in both countries.

David Rozado

Political biases in Large Language Model (LLM)-based artificial intelligence (AI) systems, such as OpenAI's ChatGPT or Google's Gemini, have been previously reported. While several prior studies have attempted to quantify these biases using political orientation tests, such approaches are limited by potential tests' calibration biases and constrained response formats that do not reflect real-world human-AI interactions. This study employs a multi-method approach to assess political bias in leading AI systems, integrating four complementary methodologies: (1) linguistic comparison of AI-generated text with the language used by Republican and Democratic U.S. Congress members, (2) analysis of political viewpoints embedded in AI-generated policy recommendations, (3) sentiment analysis of AI-generated text toward politically affiliated public figures, and (4) standardized political orientation testing. Results indicate a consistent left-leaning bias across most contemporary AI systems, with arguably varying degrees of intensity. However, this bias is not an inherent feature of LLMs; prior research demonstrates that fine-tuning with politically skewed data can realign these models across the ideological spectrum. The presence of systematic political bias in AI systems poses risks, including reduced viewpoint diversity, increased societal polarization, and the potential for public mistrust in AI technologies. To mitigate these risks, AI systems should be designed to prioritize factual accuracy while maintaining neutrality on most lawful normative issues. Furthermore, independent monitoring platforms are necessary to ensure transparency, accountability, and responsible AI development.

Waseq Billah

Social media broadly refers to digital platforms and applications that simulate social interactions online. This study investigates the impact of social media platforms and their algorithms on political interest among users. As social media usage continues to rise, platforms like Facebook and X (formerly Twitter) play increasingly pivotal roles in shaping political discourse. By employing statistical analyses on data collected from over 3,300 participants, this research identifies significant differences in how various social media platforms influence political interest. Findings reveal that moderate Facebook users demonstrate decreased political engagement, whereas even minimal engagement with X significantly boosts political interest. The study further identifies demographic variations, noting that males, older individuals, Black or African American users, those with higher incomes show greater political interest. The demographic analysis highlights that Republicans are particularly active on social media - potentially influencing their social media engagement patterns. However, the study acknowledges a crucial limitation - the lack of direct data regarding the content users are exposed to which is shaping their social media experiences. Future research should explore these influences and consider additional popular platforms to enhance the understanding of social media's political impact. Addressing these gaps can provide deeper insights into digital political mobilization, aiding policymakers, educators, and platform designers in fostering healthier democratic engagement.

Margarida Mendonca, Alvaro Figueira

Social media has reshaped political discourse, offering politicians a platform for direct engagement while reinforcing polarization and ideological divides. This study introduces a novel topic evolution framework that integrates BERTopic-based topic modeling with Moral Foundations Theory (MFT) to analyze the longevity and moral dimensions of political topics in Twitter activity during the 117th U.S. Congress. We propose a methodology for tracking dynamic topic shifts over time and measuring their association with moral values and quantifying topic persistence. Our findings reveal that while overarching themes remain stable, granular topics tend to dissolve rapidly, limiting their long-term influence. Moreover, moral foundations play a critical role in topic longevity, with Care and Loyalty dominating durable topics, while partisan differences manifest in distinct moral framing strategies. This work contributes to the field of social network analysis and computational political discourse by offering a scalable, interpretable approach to understanding moral-driven topic evolution on social media.

Gonzalo Bustamante Kuschel

This article examines the subtle nuances of Hobbes’s and Kant’s perspectives on rhetoric and materialism, contextualising them within the broader framework of political philosophy. Despite both philosophers being critics of rhetoric, their approaches exhibit notable divergences. Hobbes, who advocated for monarchy, criticized rhetoric from the perspective of a materialist anthropology influenced by Lucretius. However, he paradoxically employed rhetorical strategies in his new scientia civilis. Despite critiquing both Lucretian materialism and rhetoric, Kant incorporated certain rhetorical elements compatible with his philosophical framework, particularly in relation to Epicureanism. This study analyses their interpretations of paradiastole and the implications for the political thought. The argument is that both thinkers, in seeking a rational foundation for the political order, anchor their notions of rationality in Epicurean materialism, by reconfiguring rhetorical elements to suit their respective philosophies. The article elucidates Kant’s republican proclivities and his aspiration to maximize the citizens’ autonomy, which contrasts with Hobbes’s monarchical orientation. This research contributes to a more nuanced understanding of the early modern political thought and its relevance to the contemporary republican and democratic theory.

Giuseppe Martinico

In this article, I shall focus on the legal consequences of one of the most obvious features of populisms: identity politics. In particular, I shall explore how populists in power use constitutional law to identify and fight the alleged enemy, thus confirming their Schmittian flavour. In Schmitt, public law becomes part of a constitutional narrative that represents the people as forged by a static identity that goes back to the mythological origin of the legal system. This reconstruction is based on an organicistic reading of the concept of the people. This identitarian public law makes instrumental use of the moral argument, the historical argument and the religious argument. Populists in government tend to militarise constitutional law in many ways and in this article I will focus on two strategies: one that looks backwards, consisting of the instrumentalisation of the argument of constituent power; and one that looks forward and leverages the use of constitutional amendment.

Rainer Rehak

A lot of business and research effort currently deals with the so called decentralised ledger technology blockchain. Putting it to use carries the tempting promise to make the intermediaries of social interactions superfluous and furthermore keep secure track of all interactions. Currently intermediaries such as banks and notaries are necessary and must be trusted, which creates great dependencies, as the financial crisis of 2008 painfully demonstrated. Especially banks and notaries are said to become dispensable as a result of using the blockchain. But in real-world applications of the blockchain, the power of central actors does not dissolve, it only shifts to new, democratically illegitimate, uncontrolled or even uncontrollable power centers. As interesting as the blockchain technically is, it doesn't efficiently solve any real-world problem and is no substitute for traditional political processes or democratic regulation of power. Research efforts investigating the blockchain should be halted.

Kai-Robin Lange, Jonas Rieger, Niklas Benner et al.

From a monarchy to a democracy, to a dictatorship and back to a democracy -- the German political landscape has been constantly changing ever since the first German national state was formed in 1871. After World War II, the Federal Republic of Germany was formed in 1949. Since then every plenary session of the German Bundestag was logged and even has been digitized over the course of the last few years. We analyze these texts using a time series variant of the topic model LDA to investigate which events had a lasting effect on the political discourse and how the political topics changed over time. This allows us to detect changes in word frequency (and thus key discussion points) in political discourse.

Apoorva Lal, Mac Lockhart, Yiqing Xu et al.

Instrumental variable (IV) strategies are widely used in political science to establish causal relationships. However, the identifying assumptions required by an IV design are demanding, and it remains challenging for researchers to assess their validity. In this paper, we replicate 67 papers published in three top journals in political science during 2010-2022 and identify several troubling patterns. First, researchers often overestimate the strength of their IVs due to non-i.i.d. errors, such as a clustering structure. Second, the most commonly used t-test for the two-stage-least-squares (2SLS) estimates often severely underestimates uncertainty. Using more robust inferential methods, we find that around 19-30% of the 2SLS estimates in our sample are underpowered. Third, in the majority of the replicated studies, the 2SLS estimates are much larger than the ordinary-least-squares estimates, and their ratio is negatively correlated with the strength of the IVs in studies where the IVs are not experimentally generated, suggesting potential violations of unconfoundedness or the exclusion restriction. To help researchers avoid these pitfalls, we provide a checklist for better practice.

Petar Ivanov, Ivan Koychev, Momchil Hardalov et al.

Developing tools to automatically detect check-worthy claims in political debates and speeches can greatly help moderators of debates, journalists, and fact-checkers. While previous work on this problem has focused exclusively on the text modality, here we explore the utility of the audio modality as an additional input. We create a new multimodal dataset (text and audio in English) containing 48 hours of speech from past political debates in the USA. We then experimentally demonstrate that, in the case of multiple speakers, adding the audio modality yields sizable improvements over using the text modality alone; moreover, an audio-only model could outperform a text-only one for a single speaker. With the aim to enable future research, we make all our data and code publicly available at https://github.com/petar-iv/audio-checkworthiness-detection.

Eckehard Olbrich, Sven Banisch

The paper explores the notion of a reconfiguration of political space in the context of the rise of populism and its effects on the political system. We focus on Germany and the appearance of the new right wing party "Alternative for Germany" (AfD). Many scholars of politics discuss the rise of the new populism in Western Europe and the US with respect to a new political cleavage related to globalization, which is assumed to mainly affect the cultural dimension of the political space. As such, it might replace the older economic cleavage based on class divisions in defining the dominant dimension of political conflict. An explanation along these lines suggests a reconfiguration of the political space in the sense that (1) the main cleavage within the political space changes its direction from the economic axis towards the cultural axis, but (2) also the semantics of the cultural axis itself is changing towards globalization related topics. Using the electoral manifestos from the Manifesto project database, we empirically address this reconfiguration of the political space by comparing political spaces for Germany built using topic modeling with the spaces based on the content analysis of the Manifesto project and the corresponding categories of political goals. We find that both spaces have a similar structure and that the AfD appears on a new dimension. In order to characterize this new dimension we employ a novel technique, inter-issue consistency networks (IICN) that allow to analyze the evolution of the correlations between the political positions on different issues over several elections. We find that the new dimension introduced by the AfD can be related to the split off of a new "cultural right" issue bundle from the previously existing center-right bundle.

Budimansyah Budimansyah, Nina Herlina Lubis, Miftahul Falah

Penelitian ini bertujuan untuk menguak tata ruang Galuh Pakwan sebagai ibukota terakhir Kerajaan Galuh, sejauhmana pola ruang kota tersebut berkaitan dengan nilai-nilai kelokalan sebagaimana tergambar dalam historiografi tradisional. Dalam penelitian ini metode sejarah akan dipergunakan sebagai fitur utama agar menghasilkan suatu hasil kajian yang komprehensif, dan menggunakan teori tata kota, serta metode deskriptif-kualitatif. Minimnya sumber terkait sejarah Galuh Pakwan, wawancara secara mendalam kepada para narasumber diharapkan bisa menjadi suatu bahan analisis historis. Berdasarkan fakta di lapangan, Galuh Pakwan sebagai ibukota kerajaan berawal dari sebuah kabuyutan. Pada masa pemerintahan Niskalawastu Kancana, kabuyutan tersebut dijadikan pusat politik dengan tetap menjalankan fungsi kabuyutannya. Seiring waktu, Galuh Pakwan menjelma menjadi sebuah kota yang tata ruangnya menunjukkan representasi dan implementasi konsep kosmologi Sunda. Galuh Pakwan terbentuk oleh pola radial-konsentris menerus, sebagai gambaran kosmologi Sunda sebagaimana terungkap dalam naskah-naksah Sunda kuna. The research is not only aimed at uncovering the spatial layout of Galuh Pakwan as the last capital of Galuh Kingdom, but also at exploring how well the relationship between the urban spatial patterns and the local values as depicted in the traditional historiography. Beside having the historical methods as the main feature to produce a comprehensive study result, the study also uses the urban planning theory, as well as the descriptive qualitative methods. The historical sources related to the history of the Galuh Pakuan are very limited. As a result, the in-depth interviews with the resource persons are expected to be appropriate as the observation material for historical analysis. Based on the facts found in the field, the Galuh Pakwan as the capital of the kingdom originated from a Kabuyutan. During the reign of Niskalawastu Kancana, Kabuyutan served as a political center while maintaining its original function as Kabuyutan. As the time passed, the Galuh Pakwan was transformed into a city whose spatial layout represented and implemented the Sundanese cosmological concept. The Galuh Pakwan was formed by a continuous radial-concentric pattern, as a description of Sundanese cosmology in the ancient Sundanese manuscript.

Kobra Sangari Mohazzab, Hosein Raghfar, Mir-Hossein Mousavi et al.

I International relations are full of complexities due to their multifaceted and multilateral nature. To understand decision making processes and the payoffs of their strategies, players are enabled to utilize their capabilities to impact the strategic decision payoffs. As an example of this decision structure we can refer to the international disputes and conflicts including the sanctions. The Islamic Republic of Iran’s interests in international arena have been influenced by the changing interests of the other stakeholders in the coalition of the United States sanction against Iran. In order to analyze and predict the equilibriums of the players positions in the complex international space of the sanctions, game theory, mechanism design, multi-agent systems, and artificial intelligent as new instruments of decision theory are utilized to resolve the transactions and processes influenced by the human decisions. In this research, a policy spectrum is defined according to the strategies of Iran, the United States of America and other stakeholder’s countries. Modeling and simulating the behavior of players on this continuous spectrum which includes two extremes of capitulation and confrontation shows that in the current situation, Iran’s equilibrium and dominated strategy is emphasizing the maintenance of the current agreement in JCPOA, although this position is in the lower range of the spectrum of the current agreement. In these sanctions there is a possibility of a tragedy of the commons. In order to prevent its occurrence, the results of this study imply that the dominant strategy, given that all the players are rational, is to preserve stability, security, and integrity of Iran as a regional power. In order to achieve a stable equilibrium of the game, the stakeholders try to maximize the social welfare function instead of individual participants’ payoff. The rational strategy of Iran is to stay in JCPOA, strengthening political ties with the European players, and to empower its own military and social securities.

Ramy Baly, Giovanni Da San Martino, James Glass et al.

We explore the task of predicting the leading political ideology or bias of news articles. First, we collect and release a large dataset of 34,737 articles that were manually annotated for political ideology -left, center, or right-, which is well-balanced across both topics and media. We further use a challenging experimental setup where the test examples come from media that were not seen during training, which prevents the model from learning to detect the source of the target news article instead of predicting its political ideology. From a modeling perspective, we propose an adversarial media adaptation, as well as a specially adapted triplet loss. We further add background information about the source, and we show that it is quite helpful for improving article-level prediction. Our experimental results show very sizable improvements over using state-of-the-art pre-trained Transformers in this challenging setup.

Kakia Chatsiou, Slava Jankin Mikhaylov

Political science, and social science in general, have traditionally been using computational methods to study areas such as voting behavior, policy making, international conflict, and international development. More recently, increasingly available quantities of data are being combined with improved algorithms and affordable computational resources to predict, learn, and discover new insights from data that is large in volume and variety. New developments in the areas of machine learning, deep learning, natural language processing (NLP), and, more generally, artificial intelligence (AI) are opening up new opportunities for testing theories and evaluating the impact of interventions and programs in a more dynamic and effective way. Applications using large volumes of structured and unstructured data are becoming common in government and industry, and increasingly also in social science research. This chapter offers an introduction to such methods drawing examples from political science. Focusing on the areas where the strengths of the methods coincide with challenges in these fields, the chapter first presents an introduction to AI and its core technology - machine learning, with its rapidly developing subfield of deep learning. The discussion of deep neural networks is illustrated with the NLP tasks that are relevant to political science. The latest advances in deep learning methods for NLP are also reviewed, together with their potential for improving information extraction and pattern recognition from political science texts.

Olivier J. Walther, Steven M. Radil, David Russell et al.

Modern armed conflicts have a tendency to cluster together and spread geographically. However, the geography of most conflicts remains under-studied. To fill this gap, this article presents a new indicator that measures two key geographical properties of subnational political violence: the conflict intensity within a region on the one hand, and the spatial distribution of conflict within a region on the other. We demonstrate the indicator in North and West Africa between 1997 to 2019 to show that it can clarify how conflicts can spread from place to place and how the geography of conflict changes over time.

Олександра Гірна, Ілона Карпяк

Тіньова економіка притаманна всім без винятку економічним системам світу. Проте збільшення частки тіньової економіки створює значні перешкоди для зростання в економічній і соціальний сферах, конкурентоспроможності та інтеграції країни в міжнародний економічний простір. Дослідження масштабів тінізації є складним завданням, яке потребує великої кількості різних методів. Це пов’язано з тим, що тіньова економіка має прихований характер і проявляється по-різному залежно від сфери функціонування, що породжує складності оцінювання її частки в національній економіці. Проведено ідентифікацію переваг і недоліків методів оцінювання рівня тіньової економіки та кількісний аналіз чутливості соціально-економічного розвитку національних економік до впливу тіньової економіки. Статистично підтверджено висновок про те, що в розвинутих країнах фіксуються найнижчі рівні тіньової економіки, натомість найбідніші країни мають переважно екстремальні частки тіньового сектору економіки. Кореляційно-регресійний аналіз виявив, що серед показників соціально-економічного розвитку країн одним із найбільш чутливих до негативного впливу рівня тіньової економіки попереднього періоду є сумарний внутрішній кредит у  приватний сектор.