Hasil untuk "Social legislation"

M. Fishbein

Sally Falk Moore

S. Agrawal, R. Singh, Q. Murtaza

P. Burnap, M. Williams

Hateful and antagonistic content published and propagated via the World Wide Web has the potential to cause harm and suffering on an individual basis, and lead to social tension and disorder beyond cyber space. Despite new legislation aimed at prosecuting those who misuse new forms of communication to post threatening, harassing, or grossly offensive language - or cyber hate - and the fact large social media companies have committed to protecting their users from harm, it goes largely unpunished due to difficulties in policing online public spaces. To support the automatic detection of cyber hate online, specifically on Twitter, we build multiple individual models to classify cyber hate for a range of protected characteristics including race, disability and sexual orientation. We use text parsing to extract typed dependencies, which represent syntactic and grammatical relationships between words, and are shown to capture ‘othering’ language - consistently improving machine classification for different types of cyber hate beyond the use of a Bag of Words and known hateful terms. Furthermore, we build a data-driven blended model of cyber hate to improve classification where more than one protected characteristic may be attacked (e.g. race and sexual orientation), contributing to the nascent study of intersectionality in hate crime.

Venkatesh Murthy, S. Ramakrishna

The trending need for smarter electrical and electronic equipment (EEE) is surging globally by the year and is giving rise to huge amounts of outdated EEE going into landfills. This has caused enormous threats to our environment and the health of living beings due to its unsustainable ways of collection, treatment and disposal of waste EEE or E-waste. With increasing E-waste, the formal sectors lack infrastructure, technology and expertise required to collect and process the E-waste in an environmentally sound manner. This article is intended to bring out the global best practices in the field of E-waste management, to shed light on the importance of policy implementation, technology requirement and social awareness to arrive at a sustainable and circular economy. Although about 71% of the world’s populace has incorporated E-waste legislation, there is a need to enforce and implement a common legal framework across the globe. The article explains the gap created among the stakeholders and their knowledge on the roles and responsibilities towards a legalized E-waste management. It further explains the lack of awareness on extended producer responsibility (EPR) and producer responsibility schemes. Despite various legislations in force, numerous illegal practices such as acid leaching, open incineration, illegal dumping carried out by the informal sector are causing harm to the environment, natural resources and the safety of unorganized and unskilled labor. The article discusses the crucial need for awareness amongst stakeholders, consumer behavior and the global challenges and opportunities in this field to achieve a low-carbon, circular economy. To conclude, the article highlights the importance of common legal framework, EPR and licenses, transformation of the informal sector, benchmark technologies, responsibilities of various stakeholders and entrepreneurial opportunities to enhance the formal capacity. The article wholly advocates for transparency, accountability and traceability in the E-waste recycling chain, thus creating a greener environment and protecting our planet and natural resources for future generations.

D. Pacheco, Thomas J. Dean, David S. Payne

Celia Chen, Alex Leitch, William Jordan Conway et al.

The quality of a user's social media experience is determined both by the content they see and by the quality of the conversation and interaction around it. In this paper, we look at replies to tweets from mainstream media outlets and official government agencies and assess if they are good faith, engaging honestly and constructively with the original post, or bad faith, attacking the author or derailing the conversation. We assess automated approaches that may help in making this determination and then show that within our dataset of replies to mainstream media outlets and government agencies, bad faith interactions constitute 68.3% of all replies we studied, suggesting potential concerns about the quality of discourse in these specific conversational contexts. This is particularly true from verified accounts, where 91.7% of replies were bad faith. Given that verified accounts are algorithmically amplified, we discuss the implications of our work for understanding the user experience on social media.

Nils Schwager, Simon Münker, Alistair Plum et al.

The transition of Large Language Models (LLMs) from exploratory tools to active "silicon subjects" in social science lacks extensive validation of operational validity. This study introduces Conditioned Comment Prediction (CCP), a task in which a model predicts how a user would comment on a given stimulus by comparing generated outputs with authentic digital traces. This framework enables a rigorous evaluation of current LLM capabilities with respect to the simulation of social media user behavior. We evaluated open-weight 8B models (Llama3.1, Qwen3, Ministral) in English, German, and Luxembourgish language scenarios. By systematically comparing prompting strategies (explicit vs. implicit) and the impact of Supervised Fine-Tuning (SFT), we identify a critical form vs. content decoupling in low-resource settings: while SFT aligns the surface structure of the text output (length and syntax), it degrades semantic grounding. Furthermore, we demonstrate that explicit conditioning (generated biographies) becomes redundant under fine-tuning, as models successfully perform latent inference directly from behavioral histories. Our findings challenge current "naive prompting" paradigms and offer operational guidelines prioritizing authentic behavioral traces over descriptive personas for high-fidelity simulation.

F. A. Hayek

Valeria Widler, Barbara Kaminska, Andre C. R. Martins et al.

The increasing polarization in democratic societies is an emergent outcome of political opinion dynamics. Yet, the fundamental mechanisms behind the formation of political opinions, from individual beliefs to collective consensus, remain unknown. Understanding that a causal mechanism must account for both bottom-up and top-down influences, we conceptualize political opinion dynamics as hierarchical coarse-graining, where microscale opinions integrate into a macro-scale state variable. Using the CODA (Continuous Opinions Discrete Actions) model, we simulate Bayesian opinion updating, social identity-based information integration, and migration between social identity groups to represent higher-level connectivity. This results in coarse-graining across micro, meso, and macro levels. Our findings show that higher-level connectivity shapes information integration, yielding three regimes: independent (disconnected, local convergence), parallel (fast, global convergence), and iterative (slow, stepwise convergence). In the iterative regime, low connectivity fosters transient diversity, indicating an informed consensus. In all regimes, time-scale separation leads to downward causation, where agents converge on the aggregate majority choice, driving consensus. Critically, any degree of coherent higher-level information integration can overcome misalignment via global downward causation. The results highlight how emergent properties of the causal mechanism, such as downward causation, are essential for consensus and may inform more precise investigations into polarized political discourse.

Carlos Enrique Castro Osorio

Objetivo: validar el uso de instrumentos comerciales manuales para la detección de metales, en el proceso de búsqueda y recuperación de proyectiles y elementos metálicos durante la necropsia, a fin de ofrecer alternativas de detección inicial, fáciles y económicas, y fortalecer el proceso de búsqueda y recuperación de proyectiles y elementos metálicos en tejidos biológicos, en un modelo de cadáver humano. Introducción: recuperar evidencias es una actividad crítica durante las necropsias medicolegales; especialmente en las muertes violentas por proyectiles de armas de fuego, en las que los proyectiles y /o elementos metálicos, pueden migrar por cavidades corporales o quedar en vísceras huecas, grandes vasos, prendas, embalaje, entre otros, lo que dificulta su recuperación. Metodología: se utilizó un dispositivo manual de detección de metales para ubicar proyectiles y elementos metálicos en un cadáver; su embalaje, así como en las prendas de ropa. Se cálculo de la sensibilidad y especificidad, valor predictivo positivo y negativo general y especifico por ubicación anatómica. Resultados: se obtuvo una sensibilidad general del 83.33 % y especificidad del 100 %, Valor predictivo positivo =1, tasa de falsos positivos = 0,00; Valor Predictivo Negativo = 0,60; tasa de falsos negativos = 0,17. Para los objetos más pequeños, iguales o menores a 5 mm de diámetro especificidad = 100% y sensibilidad = 62,5%. Conclusión: Se encontró que estos dispositivos pueden ser herramientas útiles para la detección de proyectiles metálicos en necropsias, especialmente para objetos metálicos de 7 mm o más. Su aplicación en las áreas rurales o en espacios abiertos donde disponer de un equipo de rayos X no siempre es posible es factible. Para los objetos más pequeños, iguales o menores a 5 mm de diámetro, aunque la especificidad es del 100%, la sensibilidad del 62,5% en algunas áreas anatómicas, sugiere que se requiere más investigación para trabajar en el mejoramiento de la detección de estos objetos presentes en el cadáver.

David Rodríguez Guillén, Juan Antonio Clemente Soler, Juan Carlos Solano Lucas

Tourism is a strategic sector in Europe, and accessibility is not only a right but also represents a key element in achieving quality tourism. Thus, tourism can be understood as a matter of social justice and an integral strategy to improve destinations’ competitiveness and sustainability, as well as the overall tourist experience. Based on the understanding of accessibility as a fundamental principle in providing quality tourism that is free of discrimination, this study uses a structured questionnaire to comprehensively address key elements related to tourist accessibility. We identify potential actions for improvement; for example, making professionals in the field of accessibility available for consultation when creating tenders, improving aspects of European legislation, promoting best practices and information exchange, and improving sensitisation and awareness around this issue in society, the workplace, and educational institutions. In addition, the use of artificial intelligence or improved budget allocation at the European level could be highly useful.

Taeyeon Koo, Ill Hyung Jo, Suh-Jung Kang et al.

OBJECTIVES This cross-national comparative study was conducted to analyze the differences in physical activity-focused policies for older adults among South Korea, the United States, the United Kingdom, and Japan. METHODS The study examined elderly health promotion and physical activity–related legislation in each country through a review of policy documents and official reports issued by public institutions, as well as prior academic literature. A dual-framework approach was employed that integrates comparative policy analysis and framing analysis. In the comparative policy analysis, policies were assessed across six structural dimensions: policy objectives, implementing bodies, financial structure, program components, target populations, and evaluation methods. In the framing analysis, three discursive elements were investigated: how aging-related problems are defined, how policy tools are legitimized, and how perceptions of older adults are constructed within each country’s policy discourse. RESULTS While all four countries aim to extend healthy life expectancy, their policy designs and governance structures differ markedly. South Korea’s centralized approach revealed weak inter-ministerial coordination and regional disparities, along with a tendency to frame older adults as passive welfare recipients. The United States applies federal evidence-based guidelines through multilevel governance involving states and private actors, emphasizing voluntary participation. The United Kingdom promotes emotional well-being and social integration through collaborative efforts between government and community organizations. Japan adopts a scientific and preventive model focused on community sustainability, recognizing older adults as active contributors. CONCLUSIONS The findings suggest that South Korea should reinforce evidence-based and preventive strategies, empower local-level governance, and reframe its perception of older adults as autonomous participants rather than dependent recipients. These shifts are vital to building sustainable and inclusive elderly health promotion policies in the era of super-aged societies.

Takis Vidalis

With the rapid development of AI applications in the most important areas of economic, political and social life, the regime for the protection of fundamental rights has been significantly affected. This reality gives rise to initiatives for new legislation at international, supranational and national level. At the level of international law in particular, this legislation currently focuses on the formulation of general principles and guidelines. What is lacking is more specific regulation in situations where the introduction of AI causes uncertainty as to the protection of specific rights, particularly where conflicts arise between them. This article attempts to formulate proposals for such a more specific regulation, based on widely acknowledged principles of international law. Given that technological development and its impact on today’s societies know no national limitations, the adoption of this ‘next step’ in international law may well determine the smooth adaptation of AI to the values of democratic societies.

Kolek Antoni, Połeć Marta

This paper shows the activities of street performers in selected European countries from the perspective of current challenges in tax law. The research problem concerns the regulation of donations received by street performers by legal and tax legislation. The paper is the result of qualitative ethnographic fieldwork and an analysis of legal acts regulating the rights and obligations of street performers in the legal tax area. The results help to raise public awareness of both the legality of street performances and the lawful treatment of donations received from spectators. Moreover, the article promotes knowledge concerning the social benefits of donations to street performers. Furthermore, the authors highlighted contemporary trends and challenges related to street performers’ receipt of donations and how donations received in different currencies or cashless forms are taxed.

G. Davis

F. Scharpf

Tunazzina Islam, Dan Goldwasser

Grasping the themes of social media content is key to understanding the narratives that influence public opinion and behavior. The thematic analysis goes beyond traditional topic-level analysis, which often captures only the broadest patterns, providing deeper insights into specific and actionable themes such as "public sentiment towards vaccination", "political discourse surrounding climate policies," etc. In this paper, we introduce a novel approach to uncovering latent themes in social media messaging. Recognizing the limitations of the traditional topic-level analysis, which tends to capture only overarching patterns, this study emphasizes the need for a finer-grained, theme-focused exploration. Traditional theme discovery methods typically involve manual processes and a human-in-the-loop approach. While valuable, these methods face challenges in scalability, consistency, and resource intensity in terms of time and cost. To address these challenges, we propose a machine-in-the-loop approach that leverages the advanced capabilities of Large Language Models (LLMs). To demonstrate our approach, we apply our framework to contentious topics, such as climate debate and vaccine debate. We use two publicly available datasets: (1) the climate campaigns dataset of 21k Facebook ads and (2) the COVID-19 vaccine campaigns dataset of 9k Facebook ads. Our quantitative and qualitative analysis shows that our methodology yields more accurate and interpretable results compared to the baselines. Our results not only demonstrate the effectiveness of our approach in uncovering latent themes but also illuminate how these themes are tailored for demographic targeting in social media contexts. Additionally, our work sheds light on the dynamic nature of social media, revealing the shifts in the thematic focus of messaging in response to real-world events.

Sai Puppala, Ismail Hossain, Md Jahangir Alam et al.

Our study presents a multifaceted approach to enhancing user interaction and content relevance in social media platforms through a federated learning framework. We introduce personalized GPT and Context-based Social Media LLM models, utilizing federated learning for privacy and security. Four client entities receive a base GPT-2 model and locally collected social media data, with federated aggregation ensuring up-to-date model maintenance. Subsequent modules focus on categorizing user posts, computing user persona scores, and identifying relevant posts from friends' lists. A quantifying social engagement approach, coupled with matrix factorization techniques, facilitates personalized content suggestions in real-time. An adaptive feedback loop and readability score algorithm also enhance the quality and relevance of content presented to users. Our system offers a comprehensive solution to content filtering and recommendation, fostering a tailored and engaging social media experience while safeguarding user privacy.

Ismail Hossain, Sai Puppala, Md Jahangir Alam et al.

User activities can influence their subsequent interactions with a post, generating interest in the user. Typically, users interact with posts from friends by commenting and using reaction emojis, reflecting their level of interest on social media such as Facebook, Twitter, and Reddit. Our objective is to analyze user history over time, including their posts and engagement on various topics. Additionally, we take into account the user's profile, seeking connections between their activities and social media platforms. By integrating user history, engagement, and persona, we aim to assess recommendation scores based on relevant item sharing by Hit Rate (HR) and the quality of the ranking system by Normalized Discounted Cumulative Gain (NDCG), where we achieve the highest for NeuMF 0.80 and 0.6 respectively. Our hybrid approach solves the cold-start problem when there is a new user, for new items cold-start problem will never occur, as we consider the post category values. To improve the performance of the model during cold-start we introduce collaborative filtering by looking for similar users and ranking the users based on the highest similarity scores.