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.
The increasing amount of political debates and politics-related discussions calls for the definition of novel computational methods to automatically analyse such content with the final goal of lightening up political deliberation to citizens. However, the specificity of the political language and the argumentative form of these debates (employing hidden communication strategies and leveraging implicit arguments) make this task very challenging, even for current general-purpose pre-trained Language Models (LMs). To address this, we introduce a novel pre-trained LM for political discourse language called RooseBERT. Pre-training a LM on a specialised domain presents different technical and linguistic challenges, requiring extensive computational resources and large-scale data. RooseBERT has been trained on large political debate and speech corpora (11GB) in English. To evaluate its performances, we fine-tuned it on multiple downstream tasks related to political debate analysis, i.e., stance detection, sentiment analysis, argument component detection and classification, argument relation prediction and classification, policy classification, named entity recognition (NER). Our results show significant improvements over general-purpose LMs on the majority of these tasks, highlighting how domain-specific pre-training enhances performance in political debate analysis. We release RooseBERT for the research community.
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.
Andre Massahiro Shimaoka, Renato Cordeiro Ferreira, Alfredo Goldman
This study explores the integration of eXtreme Programming (XP) and the Cross-Industry Standard Process for Data Mining (CRISP-DM) in agile Data Science projects. We conducted a case study at the e-commerce company Elo7 to answer the research question: How can the agility of the XP method be integrated with CRISP-DM in Data Science projects? Data was collected through interviews and questionnaires with a Data Science team consisting of data scientists, ML engineers, and data product managers. The results show that 86% of the team frequently or always applies CRISP-DM, while 71% adopt XP practices in their projects. Furthermore, the study demonstrates that it is possible to combine CRISP-DM with XP in Data Science projects, providing a structured and collaborative approach. Finally, the study generated improvement recommendations for the company.
Resumo: O objetivo deste artigo é analisar como o rodoviarismo tornou-se um elemento nevrálgico no conjunto da política brasileira na primeira parte do chamado período de democratização, entre a queda do Estado Novo, em outubro de 1945, e o término do governo provisório de Nereu Ramos, em 1956. Ancorado na teoria de Nunes ( 1997 ) das novas gramáticas políticas nas relações entre Estado e sociedade a partir do Estado Novo (1937-1945) e em farta pesquisa empírica, procura-se demonstrar que a força política adquirida pelos agentes do rodoviarismo dependeu, em última instância, do papel assumido pelo Departamento Nacional de Estradas de Rodagem (DNER), que a todo custo buscou manter um grau substancial de “insulamento burocrático” diante da conturbada conjuntura política da época.
This study investigates the impact of economic globalization on China's climate using city-level data from 2005 to 2019. This study employs the Spatial Durbin Model (SDM) to reveal an inverted U-shaped relationship between globalization and climate impact, with carbon emissions initially increasing due to scale and composition effects. Surprisingly, the technology effect has limited effectiveness, particularly in second and third-tier cities. Another significant finding of this study is the observed positive correlation between carbon emissions in the previous and current periods. However, this trend leads to lower carbon emissions in neighbouring regions. The results of this study call for technology-focused policies and international collaborations to promote sustainable development in Chinese cities.
This paper aims to examine the complex interplay between migration, human rights, and security, focusing on the recent trends in state responses to refugee protection and the implications for international human rights standards. A qualitative analysis of current literature, policy documents, and case studies was conducted to assess the evolving political dynamics surrounding migration. The study also evaluates the roles of international organizations, such as the United Nations High Commissioner for Refugees (UNHCR), and non-governmental organizations (NGOs) in shaping refugee protection norms. Results: The findings reveal a significant rollback in state commitments to refugee protection, driven by rising nationalism and security concerns. This regression has resulted in the implementation of restrictive migration policies that prioritize national interests over humanitarian obligations, leading to increased vulnerability for displaced populations. The analysis highlights the critical role of NGOs and international bodies in advocating for refugee rights, despite facing challenges from state-centric approaches and power imbalances. Conclusions: The paper concludes that addressing the challenges at the intersection of migration, human rights, and security requires a concerted effort among states, civil society, and international organizations. By fostering collaboration and recognizing the human rights implications of migration, it is possible to develop more inclusive and compassionate policies that uphold the dignity and well-being of refugees and asylum seekers in a rapidly changing global context. give a great title for this article
مفهوم «کودک بد سرپرست» از مفاهیم نوپا در عرصۀ حقوق خصوصی است. ازآنجاکه «بد سرپرستی» آثار حقوقی و کیفریای مانند سلب صلاحیت یا مجازات کیفری سرپرست را به دنبال دارد، بررسی این مفهوم ضروری است. مفهوم بد سرپرستی در فقه بهصورت مجزا موردبررسی قرار نگرفته است؛ اما از خلال مباحث فقها می توان این مفهوم را استنتاج نمود. این مفهوم، در ضمن کلمات امام خمینی در مباحثی مانند سلب ولایت ولی، سقوط حضانت و عدالت در ارتباط با سرپرست طفل بیان شده است. همچنین این مفهوم در حقوق با کاستیها و نقایصی همراه است. قانونگذار تنها در یک مورد این اصطلاح را تبیین نموده است. گستردگی مفهوم بد سرپرستی و رد پای آن در جایجای حقوق، ضرورت بحث از مفهوم بد سرپرستی را با توجه به نیازهای روزافزون جامعه در این زمینه بیشازپیش نمایان می سازد. سؤال اصلی آن است که ضابطۀ اطلاق بد سرپرستی بر سرپرستان شرعی و قانونی کودک چیست؟ اگرچه ضابطۀ تعیینشده در فقه بسیار کلی است، با تطبیق این مسئله با حقوق می توان به تعیین برخی از مصادیق غیر حصری آن دستیافت؛ بنابراین ضابطۀ کلی در فقه آن است که عمل حرام مرتبط با وظایف والدین، موجب اطلاق بد سرپرستی بر او می گردد. اطلاق بد سرپرست لزوماً به معنای سلب ولایت از کودک نیست؛ اما به دادرس در مقام صدور حکم عادلانه، کمک شایانی می نماید.
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.
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.
Amir Hossein Shaddel, Mohammad Saeid Taslimi, Mohammad Ali Lessani Fesharaki
Objective
This study aims to identify the organizational responsibilities of managers in providing employees with “commands” and its related derivatives by examining the verses of the Holy Quran.
Methods
The methodology used in this study to explore the role of command in organizational culture in the light of the Holy Quran is the subjective research method within the Holy Quran. Hadiths, interpretive, translation, and lexical sources were also utilized to enrich the research. Thematic axes were designed, and the extracted concepts were organized under them.
Results
Competent managers issue commands by assessing the situation and considering various conditions to ensure their successful implementation. These conditions include adherence to organizational rules and regulations, clear communication of rules and commands, continuous development and self-improvement of managers, fostering an organizational environment that resembles a family where managers pay attention to employees as if they were family members, implementing an employee meal plan, managing based on individual employee characteristics, encouraging organizational participation of employees, managing the organization with trust in God (a vital value that affects all managerial duties), and employing a system of encouragement and punishment.
Conclusion
The responsibilities of managers in commanding employees within organizations encompass three distinct phases: pre-commanding, commanding, and post-commanding, each involving various components.
Political institutions and public administration (General)
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.
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.
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.
<p>The current paper explores the relationship between urban regeneration, tourism and culture, and offers a common approach that each of these three concepts can bring. The paper proposes and develops a new and integrated conceptual analytical framework. The analysis uses the example of the capital Skopje, which provides a suitable framework for interpreting the process. The study uses combined research methods and analysis to obtain a critical synthesis. Skopje has catalyzed a new example of urban regeneration driven by tourism and the ‘Skopje 2014’ project. The results show that, except for the old city’s core, which was generally refurbished with the ‘Skopje 2014’ project, new tourist values were also promoted in other peripheral municipalities of the city. The number, spatial concentration and nationality of foreign tourists have changed in the analyzed period. As well, the findings indicate changes in the geography and business of hotels/accommodation establishments and their increasing use in recent years. This study fits into the theoretical debate on the determinants of tourism/culture-led urban regeneration and provides appropriate theoretical contributions to literature, as well as a set of recommendations that can be useful for public sector authorities and policymakers.</p>
Political institutions and public administration (General)