Özgür Togay, Florian Kunneman, Javier Garcia-Bernardo
et al.
Political polarization emerges from a complex interplay of beliefs about policies, figures, and issues. However, most computational analyses reduce discourse to coarse partisan labels, overlooking how these beliefs interact. This is especially evident in online political conversations, which are often nuanced and cover a wide range of subjects, making it difficult to automatically identify the target of discussion and the opinion expressed toward them. In this study, we investigate whether Large Language Models (LLMs) can address this challenge through Target-Stance Extraction (TSE), a recent natural language processing task that combines target identification and stance detection, enabling more granular analysis of political opinions. For this, we construct a dataset of 1,084 Reddit posts from r/NeutralPolitics, covering 138 distinct political targets and evaluate a range of proprietary and open-source LLMs using zero-shot, few-shot, and context-augmented prompting strategies. Our results show that the best models perform comparably to highly trained human annotators and remain robust on challenging posts with low inter-annotator agreement. These findings demonstrate that LLMs can extract complex political opinions with minimal supervision, offering a scalable tool for computational social science and political text analysis.
Acts of political violence in the continental United States have increased dramatically in the last decade. For this rise in political violence, we are interested in where and when such incidents occur: how are the locations and times of incidents of political violence distributed across the continental United States, and what can we learn from a detailed examination of these distributions? We find the distribution of locations of political violence is neither uniform nor Poisson random, and that such locations cluster into well-defined geographic regions. Focusing on the county level we find a markedly skewed distribution of county counts of incidents of political violence. Examination of news reports and commentaries provided by the Armed Conflict Location & Event Data Project for the extreme outlier counties reveals compelling political and social background to the reported incidents of political violence. This, together with credible information on the role of social media in fomenting political violence leads us to postulate a field notion of upsetness as a major background to political violence. Using the time stamp on incidents of political violence we constructed a nearest neighbor model to predict future incidents of political violence at specific locations that involved a fatality.
Despite widespread concerns about the risks of AI-generated content (AIGC) to the integrity of social media discourse, little is known about its scale and scope, the actors responsible for its dissemination online, and the user responses it elicits. In this work, we measure and characterize the prevalence, spreaders, and emotional reception of AI-generated political images. Analyzing a large-scale dataset from Twitter/X related to the 2024 U.S. Presidential Election, we find that approximately 12% of shared images are detected as AI-generated, and around 10% of users are responsible for sharing 80% of AI-generated images. AIGC superspreaders--defined as the users who not only share a high volume of AI-generated images but also receive substantial engagement through retweets--are more likely to be X Premium subscribers, have a right-leaning orientation, and exhibit automated behavior. Their profiles contain a higher proportion of AI-generated images than non-superspreaders, and some engage in extreme levels of AIGC sharing. Moreover, superspreaders' AI image tweets elicit more positive and less toxic responses than their non-AI image tweets. This study serves as one of the first steps toward understanding the role generative AI plays in shaping online socio-political environments and offers implications for platform governance.
Since the withdrawal of the US / North Atlantic Treaty Organization (NATO) forces from Afghanistan in August 2021, Balochistan has experienced a renewed wave of terrorism with improved organisational/operational capabilities and better-equipped Balochistan Liberation Army (BLA) and Balochistan Liberation Front (BLF). The information environment of Balochistan has also undergone a rapid change in the last three years, with the Baloch population, especially the Baloch youth, becoming more accessible to the Baloch Nationalist Militant Organizations through a very efficient militant narrative creation dissemination system. This system of narrative creation based on the manipulation of facts and fabricated stories matched by a dynamic propaganda dissemination system is quickly replacing the facts with an alternative reality. It has also successfully replaced the national mainstream media and is becoming an alternative media choice for the Baloch population. The Baloch Nationalist Militant Organisations’ narrative has quickly gained popularity among domestic audiences and accrues credence from international media. An effective response mechanism is crucial to counter the far-reaching implications through a comprehensive and all-encompassing national effort.
Bibliography Entry
Iqbal, Jehanzeb. 2024. "Decoding Bots of Terrorism in Balochistan." Margalla Papers 28 (2): 63-77.
International relations, Private international law. Conflict of laws
Moldova is a borderland, lying geographically between Slavic Russia and the modern, liberal states of the European Union. Historically, it took shape after the rise of a multicultural Ottoman Empire to its south and the disintegrating remains of the old Holy Roman Empire to its west. These influences remain, but long before modern history it was on the invasion path between Eastern and Western Eurasia, which itself was divided between Orthodox Christianity and Roman Catholicism. Centuries of wars and occupation left a deep ethnic mark on Moldova, consisting of Dacian, Tartar, Roman, Greek, Ottoman, Russian, Magyar, and Jewish cultures. They all left their mark on Moldovan national identity, which was acquired by accommodating a cultural mix that required negotiation and tolerance which remains part of the Moldovan national identity today. This article looks at the “national question” around the example of Moldova.
Increasingly online platforms are becoming popular arenas of political amplification in India. With known instances of pre-organized coordinated operations, researchers are questioning the legitimacy of political expression and its consequences on the democratic processes in India. In this paper, we study an evolved form of political amplification by first identifying and then characterizing political campaigns with lexical mutations. By lexical mutation, we mean content that is reframed, paraphrased, or altered while preserving the same underlying message. Using multilingual embeddings and network analysis, we detect over 3.8K political campaigns with text mutations spanning multiple languages and social media platforms in India. By further assessing the political leanings of accounts repeatedly involved in such amplification campaigns, we contribute a broader understanding of how political amplification is used across various political parties in India. Moreover, our temporal analysis of the largest amplification campaigns suggests that political campaigning can evolve as temporally ordered arguments and counter-arguments between groups with competing political interests. Overall, our work contributes insights into how lexical mutations can be leveraged to bypass the platform manipulation policies and how such competing campaigning can provide an exaggerated sense of political divide on Indian social media.
Lisa Gutwenger, Stephan Keller, Martin Dolezal
et al.
The representation of politics in media influences societal perceptions and attitudes. Video games, as a pervasive form of media, contribute significantly to this phenomenon. In this work, we explore political themes within video games by analyzing politically-themed games on game distribution platforms including Steam. We conducted a statistical examination of games with political context to identify patterns and use this as a basis to introduce a first taxonomy to categorize and better understand the interplay between politics and video games. This taxonomy offers a first framework for analyzing political content in games and also sets a foundation for future research in this field.
Background While secular trends in high-income countries show an increase in the mean age at menopause, it is unclear if there is a similar pattern in low-income and middle-income countries (LMICs), where women’s exposure to biological, environmental and lifestyle determinants of menopause may differ. Premature (before age 40 years) and early (ages 40–44 years) menopause could have negative repercussions on later life health outcomes which in ageing societies could mean further stress on low-resource health systems. An evaluation of such trends in LMICs has been hampered by the suitability, quality and comparability of data from these countries.Methods Using 302 standardised household surveys from 1986 to 2019, we estimate trends and CIs using bootstrapping in the prevalence of premature and early menopause in 76 LMICs. We also developed a summary measure of age at menopause for women who experience menopause before the age of 50 years based on demographic estimation methods that can be used to measure menopausal status in surveys with truncated data.Results Trends indicate an increasing prevalence of early and premature menopause in LMICs, in particular in sub-Saharan Africa and South/Southeast Asia. These regions also see a suggested decline of the mean age at menopause with greater variation across continents.Conclusions This study enables the analysis of menopause timing by exploiting data generally used for the study of fertility by methodologically allowing the use of truncated data. Findings show a clear increase in prevalence of premature and early menopause in the regions with the highest fertility with possible consequences for later life health. They also show a different trend compared with high-income regions, confirming a lack of generalisability and the importance of accounting for nutritional and health transitions at the local level. This study calls for further data and research on menopause on a global scale.
Medicine (General), Infectious and parasitic diseases
Antonio F. Peralta, Pedro Ramaciotti, János Kertész
et al.
Political polarization in online social platforms is a rapidly growing phenomenon worldwide. Despite their relevance to modern-day politics, the structure and dynamics of polarized states in digital spaces are still poorly understood. We analyze the community structure of a two-layer, interconnected network of French Twitter users, where one layer contains members of Parliament and the other one regular users. We obtain an optimal representation of the network in a four-dimensional political opinion space by combining network embedding methods and political survey data. We find structurally cohesive groups sharing common political attitudes and relate them to the political party landscape in France. The distribution of opinions of professional politicians is narrower than that of regular users, indicating the presence of more extreme attitudes in the general population. We find that politically extreme communities interact less with other groups as compared to more centrist groups. We apply an empirically tested social influence model to the two-layer network to pinpoint interaction mechanisms that can describe the political polarization seen in data, particularly for centrist groups. Our results shed light on the social behaviors that drive digital platforms towards polarization, and uncover an informative multidimensional space to assess political attitudes online.
Inequality prevails in science. Individual inequality means that most perish quickly and only a few are successful, while gender inequality implies that there are differences in achievements for women and men. Using large-scale bibliographic data and following a computational approach, we study the evolution of individual and gender inequality for cohorts from 1970 to 2000 in the whole field of computer science as it grows and becomes a team-based science. We find that individual inequality in productivity (publications) increases over a scholar's career but is historically invariant, while individual inequality in impact (citations), albeit larger, is stable across cohorts and careers. Gender inequality prevails regarding productivity, but there is no evidence for differences in impact. The Matthew Effect is shown to accumulate advantages to early achievements and to become stronger over the decades, indicating the rise of a "publish or perish" imperative. Only some authors manage to reap the benefits that publishing in teams promises. The Matthew Effect then amplifies initial differences and propagates the gender gap. Women continue to fall behind because they continue to be at a higher risk of dropping out for reasons that have nothing to do with early-career achievements or social support. Our findings suggest that mentoring programs for women to improve their social-networking skills can help to reduce gender inequality.
Chase Yakaboski, Gregory Hyde, Clement Nyanhongo
et al.
AI for Science (AI4Science), particularly in the form of self-driving labs, has the potential to sideline human involvement and hinder scientific discovery within the broader community. While prior research has focused on ensuring the responsible deployment of AI applications, enhancing security, and ensuring interpretability, we also propose that promoting openness in AI4Science discoveries should be carefully considered. In this paper, we introduce the concept of AI for Open Science (AI4OS) as a multi-agent extension of AI4Science with the core principle of maximizing open knowledge translation throughout the scientific enterprise rather than a single organizational unit. We use the established principles of Knowledge Discovery and Data Mining (KDD) to formalize a language around AI4OS. We then discuss three principle stages of knowledge translation embedded in AI4Science systems and detail specific points where openness can be applied to yield an AI4OS alternative. Lastly, we formulate a theoretical metric to assess AI4OS with a supporting ethical argument highlighting its importance. Our goal is that by drawing attention to AI4OS we can ensure the natural consequence of AI4Science (e.g., self-driving labs) is a benefit not only for its developers but for society as a whole.
O presente trabalho tem por objetivo analisar o consequencialismo no processo decisório da Administração Pública no Brasil. Com as alterações provocadas na antiga Lei de Introdução ao Código Civil, hoje conhecida como LINDB – Lei de Introdução às Normas do Direito Brasileiro, a fundamentação técnica no processo decisório deixou de ser uma exigência formal voltada à função jurisdicional mas também passou a ser um requisito de validade para as atividades da gestão pública. Nesse processo de fundamentação, a teoria dos jogos pode ser uma ferramenta de alta relevância para o auxílio e fundamentação nas tomadas de decisões, principalmente quando o gestor se encontrar diante de cenários de alta complexidade como a atuação no combate à uma pandemia como a presente COVID-19. Não são mais admitidas fundamentações genéricas, meras afirmações de “busca do bem estar coletivo” ou “interesse social”, sendo necessária a demonstração das consequências das decisões e a forma de implementação das ações públicas.
Law in general. Comparative and uniform law. Jurisprudence, Political science (General)
Psychological science is increasingly influencing public policy. Behavioral public policy (BPP) was a milestone in this regard because it influenced many areas of policy in a general way. Well-being public policy (WPP) is emerging as a second domain of psychological science with general applicability. However, advocacy for WPP is criticized on ethical and political grounds. These criticisms are reminiscent of those directed at BPP over the past decade. This déjà vu suggests the need for interdisciplinary work that establishes normative principles for applying psychological science in public policy. We try to distill such principles for WPP from the normative debates over BPP. We argue that the uptake of BPP by governments was a function of its relatively strong normative and epistemic foundations in libertarian paternalism, or nudging, for short. We explain why the nudge framework is inappropriate for WPP. We then analyze how boosts offer a strict but feasible alternative framework for substantiating the legitimacy of well-being and behavioral policies. We illuminate how some WPPs could be fruitfully promoted as boosts and how they might fall short of the associated criteria.
: Immigration is a top concern among citizens across the globe. Research shows that the salience of immigration shapes voters’ political behavior, but little is known about whether it influences judicial behavior. This article theorizes that variation in issue salience influences judges’ behavior when there is a clear connection between the legal and a generally salient, politicized issue. I test this argument drawing on all Swiss asylum appeal decisions reached between 2007 and 2015. I find that higher asylum salience leads judges to decide otherwise similar asylum appeals less favorably. This effect is not restricted to judges affiliated with anti-immigrant parties, unlikely to be driven by accountability pressures, and strongest for those topics known to drive anti-immigrant sentiment in the general public. Together, these findings raise concerns that issue salience threatens the consistency of judicial decisions. The materials required to verify the computational reproducibility of the results, procedures, and in this American Journal of Political Science Dataverse Harvard Dataverse
O presente artigo tem como principal objetivo refletir e analisar a atual Política Nacional de Alfabetização (PNA), instituída em 2019, especificamente no que se refere à Educação de Jovens e Adultos (EJA). A metodologia que embasa o estudo é uma investigação documental, de natureza qualitativa, do período compreendido entre os anos de 2003 e 2019, referindo-se também às legislações anteriores que dizem respeito à EJA. O referencial teórico baseia-se nos estudos de Freire (1999); Maciel e Resende (2019); Albuquerque, Morais e Ferreira (2013), dentre outros. As principais conclusões do trabalho reconhecem que a PNA invisibiliza a EJA oferecida aos sujeitos pouco ou não escolarizados, ao mesmo tempo que propõe uma prática equivocada para a ação pedagógica alfabetizadora.
This paper summarizes the arguments and counterarguments within the scientific discussion on the generalization of the main vectors of the tax competitiveness theory’s development. The main purpose of the article is to analyze and systematize the research of scientists on the formation of tax competitiveness of the country, to identify the relationship of tax competitiveness with other economic categories, to determine the most promising areas of research on this issue. The results of trend analysis of scientific publications on tax competitiveness, indexed by Scopus and Web of Science scientometric databases, show a gradual increase in the relevance of these issues. The average growth rate of the number of publications on tax competitiveness in the Scopus database exceeds 12%, and in the Web of Science database – 45%. The methodological tools of the bibliometric analysis are VOSViewer v.1.6.10 and Scopus and Web of Science database analysis tools. The object of analysis is 4,598 publications indexed in the Web of Science database and 4,898 publications indexed in the Scopus database. The issues of international tax competitiveness became most relevant in 2003-2005, which coincided with the period of aggravation of the global economic crisis, which was accompanied by a significant reduction in tax revenues to budgets. The article identifies the top 10 Journals, most of which are indexed simultaneously by two databases and are part of the first quarter, in which the issue of tax competitiveness was considered most often. The study empirically confirms and theoretically proves the intersectoral nature of the study of the problem of the country’s tax competitiveness. According to the Web of Science database, issues of tax competitiveness were most often considered within the subject areas of Economics (39% of publications); Business Finance (6%); Environmental Studies (6%); Political Science (5%); Law (4%); Urban Studies (3%); Business (3%); Management (3%); Environmental Sciences (2%); Public Administration (2%); Regional Urban Planning (2%); International Relations (2%); Operations Research Management Science 2%) and others (21%), while according to the Scopus database – Economics, Econometrics and Finance (published 28% of all papers); Social Sciences (21%); Business, Management and Accounting (13%); Engineering (7%); Environmental Science (7%); Medicine (5%); Energy (4%); Computer Science (2%); Arts and Humanities (2%); Decision Sciences (2%); Earth and Planetary Sciences (1%); Materials Science (1%); Agricultural and Biological Sciences (1%); Others (6%). The paper clusters international research networks on tax competitiveness by geographical area and identifies 5 clusters of cooperation of scientists in the preparation of publications indexed in the Web of Science database and 4 clusters – in the preparation of publications indexed in the Scopus database. According to the results of the analysis of metadata of publications devoted to the tax competitiveness, 14672 keywords, the frequency of use of which exceeds 5, were identified and grouped into 5 patterns. Most often, the concept of tax competitiveness is associated with the concepts of tax, economics, competition, costs, taxation.
Ali Hürriyetoğlu, Vanni Zavarella, Hristo Tanev
et al.
We describe our effort on automated extraction of socio-political events from news in the scope of a workshop and a shared task we organized at Language Resources and Evaluation Conference (LREC 2020). We believe the event extraction studies in computational linguistics and social and political sciences should further support each other in order to enable large scale socio-political event information collection across sources, countries, and languages. The event consists of regular research papers and a shared task, which is about event sentence coreference identification (ESCI), tracks. All submissions were reviewed by five members of the program committee. The workshop attracted research papers related to evaluation of machine learning methodologies, language resources, material conflict forecasting, and a shared task participation report in the scope of socio-political event information collection. It has shown us the volume and variety of both the data sources and event information collection approaches related to socio-political events and the need to fill the gap between automated text processing techniques and requirements of social and political sciences.
The ongoing debate on the ethics of self-driving cars typically focuses on two approaches to answering ethical questions: moral philosophy and social science. I argue that these two approaches are both lacking. We should neither deduce answers from individual moral theories nor should we expect social science to give us complete answers. To supplement these approaches, we should turn to political philosophy. The issues we face are collective decisions that we make together rather than individual decisions we make in light of what we each have reason to value. Political philosophy adds three basic concerns to our conceptual toolkit: reasonable pluralism, human agency, and legitimacy. These three concerns have so far been largely overlooked in the debate on the ethics of self-driving cars.
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.