Hasil untuk "Political science (General)"

Thanai Permpul, Abdeel Kadir Bello, Ahmad Abdalaziz Alnusfir et al.

The article aimed to comprehensively analyse the great powers' rivalries in the current international political and geopolitical landscape, which may be leading to a changing global order. Great Power in the Changing International Order refers to the intensifying competition and conflict among the major powers, especially the US, China, and Russia. It covers various issues such as trade, technology, security, human rights and global governance. The emergence of this rivalry has challenged the existing international order, shaped mainly by the US and its allies after the Cold War. It has created new opportunities and risks for the middle and smaller powers caught between the great-power axis. The latter half of the 20th century saw a shift toward a multipolar world due to globalisation, the collapse of the Soviet Union, and technological advances. However, the 19th and 20th centuries were marked by the dynamic nature of multipolarity, with periods of stability and instability. The receding US influence, the rise of other power centres, and the transition from geopolitics to geoeconomics are among the main factors driving the transition in the world order.   Bibliography Entry Permpul, Thanai, Abdeel Kadir Bello, Ahmad Abdalaziz Alnusfir and Meshal Abdullah Salman Almaliki. 2025. "Great Power Rivalry in a Changing International Order." Margalla Papers 29 (2): 54-67.

Krishna Sharma, Khemraj Bhatt

Text-based measurement in political research often treats classi6ication disagreement as random noise. We examine this assumption using con6idence-weighted human annotations of 5,000 social media messages by U.S. politicians. We 6ind that political communication is generally highly legible, with mean con6idence exceeding 0.99 across message type, partisan bias, and audience classi6ications. However, systematic variation concentrates in the constituency category, which exhibits a 1.79 percentage point penalty in audience classi6ication con6idence. Given the high baseline of agreement, this penalty represents a sharp relative increase in interpretive uncertainty. Within messages, intent remains clear while audience targeting becomes ambiguous. These patterns persist with politician 6ixed effects, suggesting that measurement error in political text is structured by strategic incentives rather than idiosyncratic coder error.

Frederik J. Zuiderveen Borgesius, Judith Möller, Sanne Kruikemeier et al.

Online political microtargeting involves monitoring people's online behaviour, and using the collected data, sometimes enriched with other data, to show people-targeted political advertisements. Online political microtargeting is widely used in the US; Europe may not be far behind. This paper maps microtargeting's promises and threats to democracy. For example, microtargeting promises to optimise the match between the electorate's concerns and political campaigns, and to boost campaign engagement and political participation. But online microtargeting could also threaten democracy. For instance, a political party could, misleadingly, present itself as a different one-issue party to different individuals. And data collection for microtargeting raises privacy concerns. We sketch possibilities for policymakers if they seek to regulate online political microtargeting. We discuss which measures would be possible, while complying with the right to freedom of expression under the European Convention on Human Rights.

Muhammad Arslan, Saba Munawar, Christophe Cruz

In the contemporary digital landscape, media content stands as the foundation for political news analysis, offering invaluable insights sourced from various channels like news articles, social media updates, speeches, and reports. Natural Language Processing (NLP) has revolutionized Political Information Extraction (IE), automating tasks such as Event Extraction (EE) from these diverse media outlets. While traditional NLP methods often necessitate specialized expertise to build rule-based systems or train machine learning models with domain-specific datasets, the emergence of Large Language Models (LLMs) driven by Generative Artificial Intelligence (GenAI) presents a promising alternative. These models offer accessibility, alleviating challenges associated with model construction from scratch and reducing the dependency on extensive datasets during the training phase, thus facilitating rapid implementation. However, challenges persist in handling domain-specific tasks, leading to the development of the Retrieval-Augmented Generation (RAG) framework. RAG enhances LLMs by integrating external data retrieval, enriching their contextual understanding, and expanding their knowledge base beyond pre-existing training data. To illustrate RAG's efficacy, we introduce the Political EE system, specifically tailored to extract political event information from news articles. Understanding these political insights is essential for remaining informed about the latest political advancements, whether on a national or global scale.

Mahdi Goldani

Political stability is crucial for the socioeconomic development of nations, particularly in geopolitically sensitive regions such as the Gulf Cooperation Council Countries, Saudi Arabia, UAE, Kuwait, Qatar, Oman, and Bahrain. This study focuses on predicting the political stability index for these six countries using machine learning techniques. The study uses data from the World Banks comprehensive dataset, comprising 266 indicators covering economic, political, social, and environmental factors. Employing the Edit Distance on Real Sequence method for feature selection and XGBoost for model training, the study forecasts political stability trends for the next five years. The model achieves high accuracy, with mean absolute percentage error values under 10, indicating reliable predictions. The forecasts suggest that Oman, the UAE, and Qatar will experience relatively stable political conditions, while Saudi Arabia and Bahrain may continue to face negative political stability indices. The findings underscore the significance of economic factors such as GDP and foreign investment, along with variables related to military expenditure and international tourism, as key predictors of political stability. These results provide valuable insights for policymakers, enabling proactive measures to enhance governance and mitigate potential risks.

Hongzhou Chen, Xiaolin Duan, Abdulmotaleb El Saddik et al.

Harnessing the transparent blockchain user behavior data, we construct the Political Betting Leaning Score (PBLS) to measure political leanings based on betting within Web3 prediction markets. Focusing on Polymarket and starting from the 2024 U.S. Presidential Election, we synthesize behaviors over 15,000 addresses across 4,500 events and 8,500 markets, capturing the intensity and direction of their political leanings by the PBLS. We validate the PBLS through internal consistency checks and external comparisons. We uncover relationships between our PBLS and betting behaviors through over 800 features capturing various behavioral aspects. A case study of the 2022 U.S. Senate election further demonstrates the ability of our measurement while decoding the dynamic interaction between political and profitable motives. Our findings contribute to understanding decision-making in decentralized markets, enhancing the analysis of behaviors within Web3 prediction environments. The insights of this study reveal the potential of blockchain in enabling innovative, multidisciplinary studies and could inform the development of more effective online prediction markets, improve the accuracy of forecast, and help the design and optimization of platform mechanisms. The data and code for the paper are accessible at the following link: https://github.com/anonymous.

Giulio Pecile, Niccolò Di Marco, Matteo Cinelli et al.

Social media platforms significantly influence ideological divisions by enabling users to select information that aligns with their beliefs and avoid opposing viewpoints. Analyzing approximately 47 million Facebook posts, this study investigates the interactions of around 170 million users with news pages, revealing distinct patterns based on political orientations. While users generally prefer content that reflects their political biases, the extent of engagement varies even among individuals with similar ideological leanings. Specifically, political biases heavily influence commenting behaviors, particularly among users leaning towards the center-left and the right. Conversely, the 'likes' from center-left and centrist users are more indicative of their political affiliations. This research illuminates the complex relationship between social media behavior and political polarization, offering new insights into the manifestation of ideological divisions online.

Reysa Anggreyani, Suranto

This Research explores the social media used to advocate the issues in Surakarta city, in this case, using the social media specific to the Twitter data of the mayor of Surakarta, Gibran Rakabuming Raka (@gibran_tweet). This Research uses Qualitative approach and analysis data with Qualitative Data Analysis Software (Q-DAS). This Research founds that First, The social media content dichotomy of account Gibran Rakabuming Raka as Mayor of Surakarta's dominance of social media as part of reports tolls shows that social media can access everyone to report about the social infrastructure and other problems in Surakarta City. Second, the activity of the account of Gibran Rakbuming Raka focuses only on Surakarta city content. Third, the narration dominance with words related to the location Surakarta or Solo, indicated that the content of Gibran Rakabuming Raka as mayor of Surakata or Solo refers to the specific area in Solo or Surakarta, shows that the content dominance for local content of solo or Surakarta.

Mike Nkongolo

Cybersecurity in politics has emerged as a critical and intricate realm intersecting technology, governance, and international relations. In this interconnected digital context, political entities confront unparalleled challenges in securing sensitive data, upholding democratic procedures, and countering cyber threats. This study delves into the multifaceted landscape of political cybersecurity, examining the evolving landscape of cyberattacks, their impact on political stability, and strategies for bolstering digital resilience. The intricate interplay between state-sponsored hacking, disinformation campaigns, and eroding public trust underscores the imperative for robust cybersecurity measures to safeguard political system integrity. Through an extensive exploration of real-world case studies, policy frameworks, and collaborative initiatives, this research illuminates the intricate network of technological vulnerabilities, geopolitical dynamics, and ethical concerns that shape the dynamic evolution of cybersecurity in politics. Amidst evolving digital landscapes, the imperative for agile and preemptive cybersecurity strategies is paramount for upholding the stability and credibility of political institutions.

Jamie L. Molaro

Art can be a powerful tool in science engagement efforts to help facilitate learning and public discourse around space and space exploration. The Art of Planetary Science is an annual exhibition combining science and art which aims to help people to connect more meaningfully to science outside of traditional education models. Works solicited from scientists and from the public explore the beauty of the universe, as well as communicate and abstract scientific concepts from an artistic framework. These events offer the public a unique perspective on science and an opportunity to participate in dialogue around how and why we explore space. As an extension of the exhibition, a series of workshops for artists and educators focuses on techniques in creating science-driven art and how it can be used as a tool for scientific inquiry. We will discuss our success with these efforts and the important role that art can play in shaping the evolving narrative of humanity's relationship to space.

Dmitry Nikolaev, Tanise Ceron, Sebastian Padó

Scaling analysis is a technique in computational political science that assigns a political actor (e.g. politician or party) a score on a predefined scale based on a (typically long) body of text (e.g. a parliamentary speech or an election manifesto). For example, political scientists have often used the left--right scale to systematically analyse political landscapes of different countries. NLP methods for automatic scaling analysis can find broad application provided they (i) are able to deal with long texts and (ii) work robustly across domains and languages. In this work, we implement and compare two approaches to automatic scaling analysis of political-party manifestos: label aggregation, a pipeline strategy relying on annotations of individual statements from the manifestos, and long-input-Transformer-based models, which compute scaling values directly from raw text. We carry out the analysis of the Comparative Manifestos Project dataset across 41 countries and 27 languages and find that the task can be efficiently solved by state-of-the-art models, with label aggregation producing the best results.

Ricardo Pozas Horcasitas, Jorge Gutiérrez Pérez, Raúl Béjar Navarro et al.

Bagu, Sergio, Tiempo, realidad social y conocimiento, Ricardo Pozas Horcasitas Fisher, Ernst, La necesidad del arte, Jorge Gutiérrez Pérez Goldman, Lucien, La filosofía y las ciencias humanas, Jorge Gutiérrez Pérez Heilbroner, Robert L., Entre capitalismo y socialismo, Raúl Béjar Navarro Kofler, Holz y Abendroth, Conversaciones con Luckács, Miguel Bautista Jay A. Sigler, La tradición conservadora en el pensamiento de los Estados Unidos, Raúl Béjar Navarro May, Francis B., Introduction to Games of Strategy, Lian Karp Markiewicz-Lagneau, Janina, Estratificación y movilidad social en los países socialistas, Juan Manuel Cañibe Ortiz Wadgymar, Arturo, Aspectos de la economía del Istmo de Tehuantepec, Víctor de la Cruz  Varios autores, Discusiones sobre planificación, Raúl Rojas Soriano

N. N. Trubnikova, M. V. Babkova

“Konjaku monogatari-shu”, a collection of Japanese Buddhist setsuwa tales composed in XII c., has been studied by Japanese scholars using Western methodology from the end of XIX and the beginning of XX cc. That is also the time when Western scholars start mentioning it in their works. From the very beginning untill recent times publications dealing with “Konjaku” gave special attention to the appraising of the text: the authors speculated if we could put this record amidst other chefs d’oeuvres of Japanese literature, its main outcomes? Review of those speculations shows us some particularities of the history of XX c. Japanese studies. Depending on the period when this of those study was made we can find there problems of the origins of “Konjaku”, should they be found in folklore or in the literature, of the religious and artistic tasks of “Konjaku”. The answers to all these questions are determinative to a large extent for the suggestions made by scholars about the circumstances of creation of “Konjaku”, its author(s), its composition in the whole and the meaning of its particular tales.

Laetitia Duval, Elisa Sicuri, Susana Scott et al.

Abstract Background Malaria in pregnancy remains a major health threat in sub-Saharan Africa to both expectant mothers and their unborn children. To date, there have been very few studies focused on the out of pocket costs associated with seeking treatment for malaria during pregnancy. Methods A cross-sectional survey was undertaken in Burkina Faso and The Gambia to estimate the direct and indirect costs associated with outpatient consultations (OP) and inpatient admissions (IP). Direct costs were broken down into medical (admission fees, drug charges, and laboratory fees), and non-medical (transportation and food). Indirect costs reflected time lost due to illness. In total, 220 pregnant women in Burkina Faso and 263 in The Gambia were interviewed about their treatment seeking decisions, expenditure, time use and financial support associated with each malaria episode. Results In Burkina Faso 6.7% sought treatment elsewhere before their OP visits, and 27.1% before their IP visits. This compares to 1.3% for OP and 25.92% for IP in The Gambia. Once at the facility, the average direct costs (out of pocket) were 3.91US$ for an OP visit and 15.38US$ of an IP visit in Burkina Faso, and 0.80US$ for an OP visit and 9.19US$ for an IP visit in The Gambia. Inpatient direct costs were driven by drug costs (9.27US$) and transportation costs (2.72US$) in Burkina Faso and drug costs (3.44 US$) and food costs (3.44 US$) in The Gambia. Indirect costs of IP visits, valued as the opportunity cost of time lost due to the illness, were estimated at 11.85US$ in Burkina Faso and 4.07US$ in The Gambia. The difference across the two countries was mainly due to the longer time of hospitalization in Burkina Faso compared to The Gambia. In The Gambia, the vast majority of pregnant women reported receiving financial support from family members living abroad, most commonly siblings (65%). Conclusions High malaria treatment costs are incurred by pregnant women in Burkina Faso and The Gambia. Beyond the medical costs of fees and drugs, costs in terms of transport, food and time are significant drivers. The role of remittances, particularly their effect on accessing health care, needs further investigation.

Oleksandr SHNYRKOV, Oleksii CHUGAIEV

The paper assesses vulnerability of the EU exports to Ukraine to the current COVID-19 pandemic, which became the major challenge for societies and economies. The main current trends affecting the bilateral trade are discussed. A regression analysis is used to estimate the effects of demand and supply shocks, and changes in price competitiveness. The EU exports of fuels and road vehicles are the most sensitive to changes in the Ukraine's GDP, the exports of chemical products and telecommunication equipment - to devaluation of hryvnia. The most resilient EU exports to Ukraine included medicinal and pharmaceutical products, beverages and tobacco. The changes in consumption patterns under the quarantine measures also favoured stability of food and IT-services exports. The post-factum verification of results with the resent data confirmed most sector-specific effects. On average the EU exports to Ukraine turned out to be more resilient than to other countries.

Zsuzsanna Hornyik, László Jakab

Jelen tanulmány a fennálló, mindenki számára ismert helyzet – statisztikai adatokkal történő – bemutatását követően a megoldások lehetőségét kívánja számba venni, miután néhány nemzetközi szabályozási megoldást is számba vesz és a múltba is visszatekint. Mindezek mellett a közúti közlekedési balesetek magas számának okait is megpróbálja feltárni. Tekintettel arra, hogy olyan társadalmi  problémáról van szó, amely valamennyi állampolgárt érint, kiemelkedően fontos a közúti közlekedési balesetek megelőzése érdekében a közlekedés szereplőinek általános viselkedését, szokásait, esetenkénti magatartását vizsgálat tárgyává tenni. A szerzők egyelőre csak elméleti szinten közelítenek e rendkívül összetett jelenséghez, de a cikkben leírásra kerül néhány jövőbe mutató, a megelőzést szolgáló technikai lehetőség, elképzelés.

Hector Galindo-Silva

In most of the recent literature on state capacity, the significance of wars in state-building assumes that threats from foreign countries generate common interests among domestic groups, leading to larger investments in state capacity. However, many countries that have suffered external conflicts don't experience increased unity. Instead, they face factional politics that often lead to destructive civil wars. This paper develops a theory of the impact of interstate conflicts on fiscal capacity in which fighting an external threat is not always a common-interest public good, and in which interstate conflicts can lead to civil wars. The theory identifies conditions under which an increased risk of external conflict decreases the chance of civil war, which in turn results in a government with a longer political life and with more incentives to invest in fiscal capacity. These conditions depend on the cohesiveness of institutions, but in a non-trivial and novel way: a higher risk of an external conflict that results in lower political turnover, but that also makes a foreign invasion more likely, contributes to state-building only if institutions are sufficiently incohesive.

Vishnu Viswanathan, Erwan Mazarico, Stephen Merkowitz et al.

The Lunar Laser Ranging (LLR) experiment has accumulated 50 years of range data of improving accuracy from ground stations to the laser retroreflector arrays (LRAs) on the lunar surface. The upcoming decade offers several opportunities to break new ground in data precision through the deployment of the next generation of single corner-cube lunar retroreflectors and active laser transponders. This is likely to expand the LLR station network. Lunar dynamical models and analysis tools have the potential to improve and fully exploit the long temporal baseline and precision allowed by millimetric LLR data. Some of the model limitations are outlined for future efforts. Differential observation techniques will help mitigate some of the primary limiting factors and reach unprecedented accuracy. Such observations and techniques may enable the detection of several subtle signatures required to understand the dynamics of the Earth-Moon system and the deep lunar interior. LLR model improvements would impact multi-disciplinary fields that include lunar and planetary science, Earth science, fundamental physics, celestial mechanics and ephemerides.

Paul K. Byrne, David T. Blewett, Nancy L. Chabot et al.

We advocate for establishing key scientific priorities for the future of Mercury exploration, including the development of specific science goals for a landed mission. We support the Mercury science community in fostering closer collaboration with ongoing and planned exoplanet investigations. The continued exploration of Mercury should be conceived as a multi-mission, multi-generational effort, and that the landed exploration of Mercury be a high scientific priority in the coming decade.

R. Pearse, J. Hitchcock, H. Keane

Abstract Within different social science and humanities disciplines, there has been debate about the impact of feminist knowledges and scholarship by women in general. This study systematically investigates the differential impact of feminist thought on disciplinary domains in the social sciences and humanities. Using quantitative citation data from the Web of Science, we investigate the extent to which gender-related research is produced and circulated in the ‘centres’ of six disciplines: economics, history; international relations; political science; philosophy and sociology. We then analyse the production and circulation of knowledge produced in feminist disciplinary sub-fields. The study findings show gender inequality persists, evidenced by gender representation in editorial positions and authorship. The proportion of gender-related research articles published in sociology is significantly greater than in economics, history, international relations, philosophy and political science. Interdisciplinarity appears to mediate the status of feminist knowledge within disciplines. The marginalisation of feminist discipline subfields appears to be constituted through practices of strong disciplinarity.