Hasil untuk "Social pathology. Social and public welfare. Criminology"

Joel Soares de Almeida, André Moulin Dardengo, Aline Faé Stocco

Este artigo analisa o impacto do critério de renda per capita como barreira ao acesso ao Benefício de Prestação Continuada (BPC), com base em dados de requerimentos administrativos entre 2011 e 2022. A pesquisa revela que a aplicação literal desse critério, sem considerar a real situação de vulnerabilidade, exclui parcela significativa da população potencialmente elegível, contrariando os objetivos constitucionais de erradicação da pobreza e promoção da dignidade humana. Os dados do INSS indicam que o critério de renda foi responsável, em média, por quase 30% dos indeferimentos do BPC no período analisado. Medidas como a obrigatoriedade de inscrição no CadÚnico e a digitalização dos requerimentos também dificultaram o acesso, especialmente para a população de baixa renda. O estudo conclui que é urgente revisar e flexibilizar os critérios de elegibilidade, para que o BPC cumpra efetivamente seu papel como política pública voltada à redução das desigualdades sociais e ao combate à pobreza.

Joonatan Laato, Veera Schroderus, Jenna Kanerva et al.

Digitized historical archives make it possible to study everyday social life on a large scale, but the information extracted directly from text often does not directly allow one to answer the research questions posed by historians or sociologists in a quantitative manner. We address this problem in a large collection of Finnish World War II Karelian evacuee family interviews. Prior work extracted more than 350K mentions of leisure time activities and organizational memberships from these interviews, yielding 71K unique activity and organization names -- far too many to analyze directly. We develop a categorization framework that captures key aspects of participation (the kind of activity/organization, how social it typically is, how regularly it happens, and how physically demanding it is). We annotate a gold-standard set to allow for a reliable evaluation, and then test whether large language models can apply the same schema at scale. Using a simple voting approach across multiple model runs, we find that an open-weight LLM can closely match expert judgments. Finally, we apply the method to label the 350K entities, producing a structured resource for downstream studies of social integration and related outcomes.

Amr Akmal Abouelmagd, Amr Hilal

The emergence of crowdsourced data has significantly reshaped social science, enabling extensive exploration of collective human actions, viewpoints, and societal dynamics. However, ensuring safe, fair, and reliable participation remains a persistent challenge. Traditional polling methods have seen a notable decline in engagement over recent decades, raising concerns about the credibility of collected data. Meanwhile, social and peer-to-peer networks have become increasingly widespread, but data from these platforms can suffer from credibility issues due to fraudulent or ineligible participation. In this paper, we explore how social interactions can help restore credibility in crowdsourced data collected over social networks. We present an empirical study to detect ineligible participation in a polling task through AI-based graph analysis of social interactions among imperfect participants composed of honest and dishonest actors. Our approach focuses solely on the structure of social interaction graphs, without relying on the content being shared. We simulate different levels and types of dishonest behavior among participants who attempt to propagate the task within their social networks. We conduct experiments on real-world social network datasets, using different eligibility criteria and modeling diverse participation patterns. Although structural differences in social interaction graphs introduce some performance variability, our study achieves promising results in detecting ineligibility across diverse social and behavioral profiles, with accuracy exceeding 90% in some configurations.

Alon Bebchuk

We study the problem of allocating a set of indivisible items to agents with supermodular utilities to maximize the Nash social welfare. We show that the problem is NP-hard for any approximation factor.

Blaž Rodič

This study presents a review of research on social media bot detection. Social media bots are used by political and criminal actors for mass distribution of political messages, as well as rumors, conspiracy theories, and other forms of false information. Through the spread of disinformation, bots are eroding the public trust in political and media institutions and integrity of social media. We have examined recent research publication in the field of social media bot detection, including several previous reviews of bot detection research, and identified the methods used in bot detection and issues encountered by researchers. Our review was conducted through a search of 5 main bibliographical databases, which has produced a total of 534 research papers and other publications. This collection was then filtered with exclusion and inclusion criteria to isolate the most pertinent documents, resulting in a focused selection of 49 documents that were analyzed for this review. In the first part of the paper we introduce the phenomenon of fake news within social networks, its connection with social media bot activity, and conclude the introduction with issues caused or exacerbated by bots. In the main part of this paper we first present the results of statistical analysis of the reviewed documents and then introduce the field of social media bot research, followed by an overview of the issues of social media bot detection identified in the reviewed literature, including the evolution of bot concealment techniques and the methodological issues presented in some of the bot detection studies. We then proceed with an overview of the methods and results from the reviewed research papers, structured according to the main methodology used in the examined studies. Our review concludes with examination of the recent trends in social media bot development and related bot detection research.

Shamikh Badra

This article contributes to the study of settler colonialism and Indigenous resistance by introducing a novel framework: “Indigenous Diplomatic Resistance” (IDR). Michel Foucault’s theories are useful for highlighting how Indigenous groups use diplomatic channels to resist settler-colonial domination. By applying settler colonialism theory to the Palestinian case, this article offers new insights into Palestinian resistance against colonial Zionism, especially in the time of Jewish immigration between 1882 to 1914. Foucault’s notion of discursive power underscores how colonial powers impose knowledge systems that justify control, whilst Indigenous peoples push back through alternate forms of knowledge, including diplomatic strategies ( Foucault 2003 : 23–24). This article challenges narratives that focus on military or grassroots resistance, suggesting that Palestinian diplomatic resistance was central to their resistance strategy. This approach provides a new lens through which to understand the nature of Palestinian resistance, emphasizing the epistemic struggle inherent in their fight against settler colonialism.

فاطمه ارمان, شیرین احمدنیا, منصور فتحی

بارداری دوره‌ای همراه با تغییرات گسترده در زندگی خانواده‌ها است که مستلزم تطابق و مقابله با چالش‌های جدید است. مددکاران اجتماعی با توجه به تخصص خود در حوزه خدمات اجتماعی، نقش کلیدی در ارائه مراقبت‌های جامع دوران بارداری ایفا می‌کنند. با این وجود، پژوهشی جامع درباره نقش مددکاران اجتماعی و رویکردهای نظری آن‌ها در دوران بارداری (پری‌ناتال) در ایران وجود ندارد. این مطالعه مروری نظام‌مند، با هدف شناسایی این نقش‌ها و رویکردها، ۱۷ مقاله بین‌المللی منتشرشده بین سال‌های ۲۰۱۰ تا ۲۰۲۳ را بررسی کرده است. نتایج نشان می‌دهند که مددکاران اجتماعی از نظریه‌های متنوعی، به‌ویژه نظریه‌های تعاملی و اجتماعی، بهره می‌برند. همچنین، این پژوهش تأکید می‌کند که عدالت اجتماعی محور اصلی فعالیت‌های مددکاری اجتماعی پری‌ناتال است. مددکاران با استفاده از نظریه‌هایی مانند فمینیستی، تبعیض نژادی، و توانمندسازی، برای کاهش نابرابری‌های اجتماعی و بهداشتی و ارتقای رفاه مادران، به‌ویژه مادران محروم، تلاش می‌کنند. نتایج این پژوهش بر اهمیت رویکردهای چندوجهی و مبتنی بر جامعه در مداخلات مددکاری اجتماعی دوران بارداری تأکید دارد. همچنین، همکاری بین‌حرفه‌ای مددکاران اجتماعی با سایر متخصصان سلامت برای ارائه خدمات جامع و مؤثر به مادران و نوزادان ضروری است. یافته‌های این مطالعه می‌تواند مبنایی برای بهبود کیفیت خدمات و توسعه برنامه‌های مداخله‌ای در حوزه مددکاری اجتماعی دوران بارداری در ایران باشد.

Vibhor Agarwal, Aravindh Raman, Nishanth Sastry et al.

The recent development of decentralised and interoperable social networks (such as the "fediverse") creates new challenges for content moderators. This is because millions of posts generated on one server can easily "spread" to another, even if the recipient server has very different moderation policies. An obvious solution would be to leverage moderation tools to automatically tag (and filter) posts that contravene moderation policies, e.g. related to toxic speech. Recent work has exploited the conversational context of a post to improve this automatic tagging, e.g. using the replies to a post to help classify if it contains toxic speech. This has shown particular potential in environments with large training sets that contain complete conversations. This, however, creates challenges in a decentralised context, as a single conversation may be fragmented across multiple servers. Thus, each server only has a partial view of an entire conversation because conversations are often federated across servers in a non-synchronized fashion. To address this, we propose a decentralised conversation-aware content moderation approach suitable for the fediverse. Our approach employs a graph deep learning model (GraphNLI) trained locally on each server. The model exploits local data to train a model that combines post and conversational information captured through random walks to detect toxicity. We evaluate our approach with data from Pleroma, a major decentralised and interoperable micro-blogging network containing 2 million conversations. Our model effectively detects toxicity on larger instances, exclusively trained using their local post information (0.8837 macro-F1). Our approach has considerable scope to improve moderation in decentralised and interoperable social networks such as Pleroma or Mastodon.

Zexun Jiang, Yafang Shi, Maoxu Li et al.

In this paper, we introduce a multi-agent simulation framework Casevo (Cognitive Agents and Social Evolution Simulator), that integrates large language models (LLMs) to simulate complex social phenomena and decision-making processes. Casevo is designed as a discrete-event simulator driven by agents with features such as Chain of Thoughts (CoT), Retrieval-Augmented Generation (RAG), and Customizable Memory Mechanism. Casevo enables dynamic social modeling, which can support various scenarios such as social network analysis, public opinion dynamics, and behavior prediction in complex social systems. To demonstrate the effectiveness of Casevo, we utilize one of the U.S. 2020 midterm election TV debates as a simulation example. Our results show that Casevo facilitates more realistic and flexible agent interactions, improving the quality of dynamic social phenomena simulation. This work contributes to the field by providing a robust system for studying large-scale, high-fidelity social behaviors with advanced LLM-driven agents, expanding the capabilities of traditional agent-based modeling (ABM). The open-source code repository address of casevo is https://github.com/rgCASS/casevo.

Aditya Surve, Archit Rathod, Mokshit Surana et al.

Multiagent social network simulations are an avenue that can bridge the communication gap between the public and private platforms in order to develop solutions to a complex array of issues relating to online safety. While there are significant challenges relating to the scale of multiagent simulations, efficient learning from observational and interventional data to accurately model micro and macro-level emergent effects, there are equally promising opportunities not least with the advent of large language models that provide an expressive approximation of user behavior. In this position paper, we review prior art relating to social network simulation, highlighting challenges and opportunities for future work exploring multiagent security using agent-based models of social networks

Yasuko Kawahata

Recent research has developed the Ising model from physics, especially statistical mechanics, and it plays an important role in quantum computing, especially quantum annealing and quantum Monte Carlo methods. The model has also been used in opinion dynamics as a powerful tool for simulating social interactions and opinion formation processes. Individual opinions and preferences correspond to spin states, and social pressure and communication dynamics are modeled through interactions between spins. Quantum computing makes it possible to efficiently simulate these interactions and analyze more complex social networks.Recent research has incorporated concepts from quantum information theory such as Graph State, Stabilizer State, and Surface Code (or Toric Code) into models of opinion dynamics. The incorporation of these concepts allows for a more detailed analysis of the process of opinion formation and the dynamics of social networks. The concepts lie at the intersection of graph theory and quantum theory, and the use of Graph State in opinion dynamics can represent the interdependence of opinions and networks of influence among individuals. It helps to represent the local stability of opinions and the mechanisms for correcting misunderstandings within a social network. It allows us to understand how individual opinions are subject to social pressures and cultural influences and how they change over time.Incorporating these quantum theory concepts into opinion dynamics allows for a deeper understanding of social interactions and opinion formation processes. Moreover, these concepts can provide new insights not only in the social sciences, but also in fields as diverse as political science, economics, marketing, and urban planning.

Patrícia Silveira da Silva, Katie Silene Cáceres Arguello

O trabalho tem como objetivo geral analisar o conteúdo das decisões publicadas pelo Tribunal de Justiça de São Paulo sobre a internação provisória de adolescentes em conflito com a lei, a partir de uma abordagem criminológica crítica. Assim, este trabalho pretende responder o seguinte problema de pesquisa: como o TJ/SP decidiu sobre a internação provisória de adolescentes em conflito com a lei durante a pandemia? Optou-se pela análise de conteúdo dos acórdãos publicados no mês de agosto de 2020, por ter sido o mês com o maior número de decisões publicadas sobre o tema. O método de exploração de literatura e de análise de conteúdo foram utilizados para a construção da pesquisa. A conclusão aponta que o TJ/SP, apesar da pandemia, contrariou a legislação e as recomendações sobre o tema, reproduziu discursos paternalistas, subverteu a excepcionalidade da internação em regra, e mitigou a saúde e a liberdade de adolescentes ao, majoritariamente, estender o prazo da internação provisória.

Graham Connelly

This is now the third SJRCC editorial I have written during the COVID-19 pandemic. Since the last issue, several vaccines have received approval from regulatory authorities and the news on their efficacy is very good. The World Health Organization reports (18 February 2021) that seven vaccines are being deployed, and more than 200 vaccines are in development, more than 60 of which are at clinical research stages. Wealthier countries are farther along in vaccine roll-out, with Israel and the UK out in front. The real challenge is to ensure equitable distribution on a world scale. The WHO has developed the COVAX Facility as a mechanism for pooling vaccine procurement and distribution to middle and low-income countries.

Wenzheng Li, Jan Vondrák

We present a $380$-approximation algorithm for the Nash Social Welfare problem with submodular valuations. Our algorithm builds on and extends a recent constant-factor approximation for Rado valuations.

Jaehyuk Park, Bogdan State, Monica Bhole et al.

Due to their essential role as places for socialization, "third places" - social places where people casually visit and communicate with friends and neighbors - have been studied by a wide range of fields including network science, sociology, geography, urban planning, and regional studies. However, the lack of a large-scale census on third places kept researchers from systematic investigations. Here we provide a systematic nationwide investigation of third places and their social networks, by using Facebook pages. Our analysis reveals a large degree of geographic heterogeneity in the distribution of the types of third places, which is highly correlated with baseline demographics and county characteristics. Certain types of pages like "Places of Worship" demonstrate a large degree of clustering suggesting community preference or potential complementarities to concentration. We also found that the social networks of different types of social place differ in important ways: The social networks of 'Restaurants' and 'Indoor Recreation' pages are more likely to be tight-knit communities of pre-existing friendships whereas 'Places of Worship' and 'Community Amenities' page categories are more likely to bridge new friendship ties. We believe that this study can serve as an important milestone for future studies on the systematic comparative study of social spaces and their social relationships.

Lavinia Serrani, Michele Tiraboschi

El artículo se centra en el análisis de la jurisprudencia italiana en cuanto al uso del teléfono móvil como causa de aparición de enfermedades profesionales. Los Autores llegan a afirmar que en la actualidad la orientación consolidada de la jurisprudencia parece inclinarse hacia la convicción de que un cierto grado de certeza probabilística pueda considerarse suficiente para reconstruir el nexo causal entre la exposición a ciertos riesgos y la aparición de enfermedades para el reconocimiento de una pensión por enfermedad profesional al trabajador. Según los Autores, esta evidencia confirmaría el retraso de la reflexión de la legislación laboral con respecto al tema de los nuevos riesgos derivados de tecnologías cuyos efectos en las personas se desconocen -mucho más allá del caso del uso de teléfonos móviles y smartphone- con especial referencia a los nuevos entornos de trabajo, los espacios de coworking y la dinámica del trabajo a distancia (el llamado smart working). De hecho, un punto de partida sólido para repensar un sistema de protecciones podría ser fomentar un diálogo interdisciplinario más fructífero entre la investigación médico-científica, la autoridad administrativa y la ciencia jurídica

Frederik Florenz, Frederik Florenz

D. G. Asatryan

The paper addresses the problem of assessing the quality of fingerprint images using spatial analysis methods. The author proposes using the previously developed mathematical model to describe the set of magnitudes of the image gradient. The model is based on the two-parameter Weibull distribution. The author proposes two approaches to assess the quality of fingerprints. The first approach is implemented by the so-called “Full reference method”, which compares the Weibull distribution parameters’ values of statistical estimates. The results of identifying sweat pores using this method are presented. The second approach is called the “No-Reference method” and is used to assess fingerprints’ quality when analyzing and identifying the information content of their individual sections. It is proposed to use an image blur map as a quality characteristic and a statistical estimate of the Weibull distribution shape parameter as a measure of the blur. The shape parameter is estimated at each image point by the combination of magnitudes of the image gradient in the vicinity of the point; in this, the previously developed blur mapping technique is applied. The specific examples illustrate effectiveness of the proposed approaches.

Ram Sewak Dubey, Giorgio Laguzzi

Total social welfare relations satisfying Pareto and equity principles on infinite utility streams has revealed a non-constructive nature. In this paper we study more deeply the needed fragment of AC. In particular, we show that such relations need a strictly larger fragment of AC than non-Lebesgue and non-Ramsey sets. We also prove a connection with the Baire property, answering Problem 11.14 posed in "Flutters and chameleon", by Mathias et al.

Yanbing Mao, Naira Hovakimyan, Tarek Abdelzaher et al.

This paper studies social system inference from a single trajectory of public evolving opinions, wherein observation noise leads to the statistical dependence of samples on time and coordinates. We first propose a cyber-social system that comprises individuals in a social network and a set of information sources in a cyber layer, whose opinion dynamics explicitly takes confirmation bias, novelty bias and process noise into account. Based on the proposed social model, we then study the sample complexity of least-square auto-regressive model estimation, which governs the number of observations that are sufficient for the identified model to achieve the prescribed levels of accuracy and confidence. Building on the identified social model, we then investigate social inference, with particular focus on the weighted network topology, the subconscious bias and the model parameters of confirmation bias and novelty bias. Finally, the theoretical results and the effectiveness of the proposed social model and inference algorithm are validated by the US Senate Member Ideology data.