Hasil untuk "Social legislation"

Alessandro Serpe

Being characterised by the centrality of legislation, one may say that Western legal theories have been grounded on a sort of Kahneman’s System 2 rational thinking. In his researches on the nature of thought, choice and decision, Kahneman has outlined how two different mental processes (heuristics-fact System 1; deliberate-slow System 2) interact within reasoning and decision-making (Kahneman 2011). Over the past decades, a number of inquiries on normative practical reasoning has grown widely. For instance, in the field of moral psychology, it has gone from views of morality based on abstract rules to perspectives emphasising the coexistence of additional factors in moral deliberation (Haidt 2001; Greene 2004). Brought to the legal domain, such inquiries have shown that the judicial-decision process is more alive to the influence of heuristics and cognitive social biases, then generally admitted. Indeed, since the early decades of 20th century, realist legal scholars such as Jerome Frank (1949a, 1949b) and Alf Ross (1946, 1959) explored the psychological grounds of judicial decision-making. Reassessed with new sensitivity, their insights prove that a realist view is the most viable alternative in both theories of legal sources and judicial adjudication, by keeping pace with the latest advancements afforded by cognitive science.

Zexu Li, M. Amin Rahimian, Lei Fang

Collective foragers, from animals to robotic swarms, must balance exploration and exploitation to locate sparse resources efficiently. While social learning is known to facilitate this balance, how the range of information sharing shapes group-level outcomes remains unclear. Here, we develop a minimal collective foraging model in which individuals combine independent exploration, local exploitation, and socially guided movement. We show that foraging efficiency is maximized at an intermediate social learning range, where groups exploit discovered resources without suppressing independent discovery. This optimal regime also minimizes temporal burstiness in resource intake, reducing starvation risk. Increasing social learning range further improves equity among individuals but degrades efficiency through redundant exploitation. Introducing risky (negative) targets shifts the optimal range upward; in contrast, when penalties are ignored, randomly distributed negative cues can further enhance efficiency by constraining unproductive exploration. Together, these results reveal how local information rules regulate a fundamental trade-off between efficiency, stability, and equity, providing design principles for biological foraging systems and engineered collectives.

Maxence Morin, Baptiste Hemery, Fabrice Jeanne et al.

Social network analysis is pivotal for organizations aiming to leverage the vast amounts of data generated from user interactions on social media and other digital platforms. These interactions often reveal complex social structures, such as tightly-knit groups based on common interests, which are crucial for enhancing service personalization or fraud detection. Traditional methods like community detection and graph matching, while useful, often fall short of accurately identifying specific groups of users. This paper introduces a novel framework specifically designed to identify groups of users within transactional graphs by focusing on the contextual and structural nuances that define these groups.

Luca Luceri, Jinyi Ye, Julie Jiang et al.

Understanding susceptibility to online influence is crucial for mitigating the spread of misinformation and protecting vulnerable audiences. This paper investigates susceptibility to influence within social networks, focusing on the differential effects of influence-driven versus spontaneous behaviors on user content adoption. Our analysis reveals that influence-driven adoption exhibits high homophily, indicating that individuals prone to influence often connect with similarly susceptible peers, thereby reinforcing peer influence dynamics, whereas spontaneous adoption shows significant but lower homophily. Additionally, we extend the Generalized Friendship Paradox to influence-driven behaviors, demonstrating that users' friends are generally more susceptible to influence than the users themselves, de facto establishing the notion of Susceptibility Paradox in online social influence. This pattern does not hold for spontaneous behaviors, where friends exhibit fewer spontaneous adoptions. We find that susceptibility to influence can be predicted using friends' susceptibility alone, while predicting spontaneous adoption requires additional features, such as user metadata. These findings highlight the complex interplay between user engagement and characteristics in spontaneous content adoption. Our results provide new insights into social influence mechanisms and offer implications for designing more effective moderation strategies to protect vulnerable audiences.

M. Ramezani, M. Bashiri, R. Tavakkoli-Moghaddam

B. Stahl, A. Andreou, P. Brey et al.

Abstract The technical and economic benefits of artificial intelligence (AI) are counterbalanced by legal, social and ethical issues. It is challenging to conceptually capture and empirically measure both benefits and downsides. We therefore provide an account of the findings and implications of a multi-dimensional study of AI, comprising 10 case studies, five scenarios, an ethical impact analysis of AI, a human rights analysis of AI and a technical analysis of known and potential threats and vulnerabilities. Based on our findings, we separate AI ethics discourse into three streams: (1) specific issues related to the application of machine learning, (2) social and political questions arising in a digitally enabled society and (3) metaphysical questions about the nature of reality and humanity. Human rights principles and legislation have a key role to play in addressing the ethics of AI. This work helps to steer AI to contribute to human flourishing.

Yavuz Agan, M. F. Acar, A. Borodin

Chan Eugene

In the age of online social platforms, increasing interactions beyond the wildest imagination, dealing with fake news has been the most challenging. Perhaps the most visible victims of fake news today are political individuals and institutions. The delicate balance between regulation and respect of individual rights and maintenance of constitutionalism in various countries today creates a unique regulatory dilemma that allows for fake news and the use of it to continue thriving. At the same time, politicians and other institutions occupy a critical role in creating legislation towards combatting fake news. Such moves could significantly undermine the ability to observe some of the fundamental rights of individuals and the overall rule of democracy [1]. Misinformation and other cases of fake news have a relatively significant impact on societies. However, resolving fake news has proved not to be easy because of numerous issues, among them, being the need to preserve fundamental rights [2]. Desktop-based research has been conducted to achieve the objectives of this research. Critical to note that most of the information vital in completing this research is electronically availed. Hence, secondary sources of information have been utilized to reach conclusions on the existence of regulations and its effectiveness toward combating fake news in the three jurisdictions.

Davide Bazzana, Nicola Comincioli, Cristina El Khoury et al.

The Water–Energy–Food (WEF) nexus describes natural resource use in the context of social needs and economic development, addressing food, water, and energy security. Population growth and rising economic prosperity will increase the demand for energy, food, and water in the Mediterranean region, compromising the sustainable use of resources. As governments are required to make decisions in order to cope with increasing demands for resources, this paper performs a review of the legislation and WEF policies, identifying the main political and institutional actors involved and the possible policy (in)coherence in four MED countries located on two continents: Egypt, Italy, Spain, and Tunisia. This choice will allow the identification of the barriers and catalysts influencing the implementation of WEF policies and will improve our understanding of the WEF trade-offs and synergies by exploring them on national, regional, and local scales.

Liam Hebert, Gaurav Sahu, Yuxuan Guo et al.

We present the Multi-Modal Discussion Transformer (mDT), a novel methodfor detecting hate speech in online social networks such as Reddit discussions. In contrast to traditional comment-only methods, our approach to labelling a comment as hate speech involves a holistic analysis of text and images grounded in the discussion context. This is done by leveraging graph transformers to capture the contextual relationships in the discussion surrounding a comment and grounding the interwoven fusion layers that combine text and image embeddings instead of processing modalities separately. To evaluate our work, we present a new dataset, HatefulDiscussions, comprising complete multi-modal discussions from multiple online communities on Reddit. We compare the performance of our model to baselines that only process individual comments and conduct extensive ablation studies.

A. Mclellan

D. Nepstad, C. Stickler, O. Almeida

Mariela Contreras, Gracia M. Pineda , Ana Romero et al.

Introducción: El rol de la mujer en el área científica ha crecido con el paso de los años, pero aún persiste una gran brecha de género en ciencia. Para conocer y manejar esa brecha, es necesario hacer un mapeo de la situación de las mujeres investigadoras en Honduras. Objetivo: Describir la participación y contribuciones de las investigadoras hondureñas en la producción científica nacional según su perfil en Google Académico. Metodología: Se usó Power BI para analizar las variables sexo, institución, índice H, número de citaciones, número de publicaciones, año de la primera publicación, y áreas de investigación registradas en su perfil, utilizando la versión 2 del Ranking de Investigadores Hondureños según su Perfil de Google Académico disponible en https://bit.ly/38s6YuT, el cual es un registro depurado. Resultados: El 35% de todos los perfiles eran de mujeres, 41% vinculadas a las ciencias médicas y de la salud y en su mayoría (92%), afiliadas a universidades. Pese al creciente número de mujeres investigadoras registradas en Google Académico, el crecimiento no es simétrico respecto a los hombres. Solamente el 3.1% de las investigadoras tenía un índice H que supera los dos dígitos. Conclusión: A pesar de los avances, se mantiene la inequidad de género entre investigadores hondureños según la data de Google Académico. Se requiere de políticas públicas e institucionales, para corregir esa brecha.

Gustavo de la Orden

El artículo analiza el impacto de la Corte Interamericana en los procesos de justicia transicional de los seis países del Cono Sur tras los gobiernos de dictadura de las décadas de 1970 y 1980. El objetivo es determinar la relevancia de la reconstrucción del contexto histórico en la jurisprudencia interamericana con relación a la erradicación de la violencia institucional practicada por los regímenes de facto. El estudio se realiza sobre diez sentencias condenatorias: se identifica su común denominador y se determinan cuáles han sido las medidas adoptadas por los Estados frente a tales condenas, especialmente aquellas que han supuesto reformas estructurales y sistémicas. Este análisis propone demostrar que la reconstrucción de los contextos históricos, estatales y regional, en las sentencias de la Corte Interamericana ha sido una herramienta fundamental para extender los alcances de su jurisprudencia a los procesos de justicia transicional de toda la región, más allá de los casos individuales denunciados y de los Estados condenados.

Yelena Mejova, Jisun An, Gianmarco De Francisci Morales et al.

The United States have some of the highest rates of gun violence among developed countries. Yet, there is a disagreement about the extent to which firearms should be regulated. In this study, we employ social media signals to examine the predictors of offline political activism, at both population and individual level. We show that it is possible to classify the stance of users on the gun issue, especially accurately when network information is available. Alongside socioeconomic variables, network information such as the relative size of the two sides of the debate is also predictive of state-level gun policy. On individual level, we build a statistical model using network, content, and psycho-linguistic features that predicts real-life political action, and explore the most predictive linguistic features. Thus, we argue that, alongside demographics and socioeconomic indicators, social media provides useful signals in the holistic modeling of political engagement around the gun debate.

Preslav Nakov, Firoj Alam, Yifan Zhang et al.

Fighting the ongoing COVID-19 infodemic has been declared as one of the most important focus areas by the World Health Organization since the onset of the COVID-19 pandemic. While the information that is consumed and disseminated consists of promoting fake cures, rumors, and conspiracy theories to spreading xenophobia and panic, at the same time there is information (e.g., containing advice, promoting cure) that can help different stakeholders such as policy-makers. Social media platforms enable the infodemic and there has been an effort to curate the content on such platforms, analyze and debunk them. While a majority of the research efforts consider one or two aspects (e.g., detecting factuality) of such information, in this study we focus on a multifaceted approach, including an API,\url{https://app.swaggerhub.com/apis/yifan2019/Tanbih/0.8.0/} and a demo system,\url{https://covid19.tanbih.org}, which we made freely and publicly available. We believe that this will facilitate researchers and different stakeholders. A screencast of the API services and demo is available.\url{https://youtu.be/zhbcSvxEKMk}

Konrad Kołodziejski

An Authoritarian Course: The Restriction of Civil Rights in Russia after 2012 This article regards the issue of Russian civil rights legislation, which has become very repressive after 2012. It focuses on legal restriction of all political and social activities that are beyond the control of the authorities, in particular the freedom of public meetings. Another goal of the Kremlin's repressive policy is the Internet, which has become the only space for freedom of speech in Russia. The new legislation tries to prevent this by two mechanisms: censorship and self-censorship. The consistent restriction of freedom of speech in Russia proves the growing anxiety of the ruling group, which fears that in the conditions of the deteriorating economic situation, it may lose control over public mood. The analysis of the legislation against civil rights in Russia shows that in recent years the scope of these rights has been constantly reduced. This leads to the conclusion that the main goal of the discussed changes in the law is the complete elimination of independent civic activity perceived as one of the main threats to the authorities.

Annette Kaspar, Sione Pifeleti, Carlie Driscoll

Abstract Background Translation and cultural adaptation of health resources is an integral part of good health-policy development and health program implementation. As part of our efforts to address ear disease and hearing loss in the Pacific Islands, we promote the translation an cultural adaptation of hearing-related questionnaires into local languages and cultural contexts. The Pacific Islands have among the highest rates of ear and hearing disorders in the world and, given the scarcity of ear/hearing health professionals in the region, a public health approach that uses appropriately translated ear/hearing health resources is highly recommended to tackle this health issue. Although formal translation and culturally adaption of hearing-related questionnaires may seem a cumbersome process, the aim of this commentary is to illustrate the potential benefits of translating two audiology questionnaires for our use in Samoa. We have carefully selected questionnaires that will serve multiple purposes (i.e., clinical, epidemiology, monitoring and evaluation, evidence-based health policy formulation and implementation), thus making the process ultimately beneficial and worthwhile. Main body The leading cause of preventable hearing loss among Samoan adolescents and young people is excessive noise exposure to recreational and environmental noise. The Youth Attitude to Noise Scale is a validated tool that assess knowledge and attitudes of adolescents towards recreational and environmental noise, and a Samoan version should provide preliminary data to guide health promotion activities for adolescents on noise-induced hearing loss. The leading cause of hearing disability among older adult Samoans is age-related hearing loss. The Revised Hearing Handicap Inventory is a tool that assess the emotional and social/situational impact of hearing difficulty among older adults, and a Samoan version should provide preliminary data to guide the development of auditory rehabilitation services. Conclusion Investment in quality translations and cultural adaptations of hearing-related questionnaires is essential for the development of audiology services that are relevant to their Pacific Island context. The use of formally translated audiology questionnaires in research studies will optimise data quality, leading to improved hearing health promotion activities, as well as provision of evidence for advocacy for public health noise policy legislation.

Yiding Cao, Yingjun Dong, Minjun Kim et al.

Collective idea generation and innovation processes are complex and dynamic, involving a large amount of qualitative narrative information that is difficult to monitor, analyze, and visualize using traditional methods. In this study, we developed three new visualization methods for collective idea generation and innovation processes and applied them to data from online social network experiments. The first visualization is the Idea Cloud, which helps monitor collective idea posting activity and intuitively tracks idea clustering and transition. The second visualization is the Idea Geography, which helps understand how the idea space and its utility landscape are structured and how collaboration was performed in that space. The third visualization is the Idea Network, which connects idea dynamics with the social structure of the people who generated them, displaying how social influence among neighbors may have affected collaborative activities and where innovative ideas arose and spread in the social network.

Mohit Singhal, Nihal Kumarswamy, Shreyasi Kinhekar et al.

Prior work has extensively studied misinformation related to news, politics, and health, however, misinformation can also be about technological topics. While less controversial, such misinformation can severely impact companies' reputations and revenues, and users' online experiences. Recently, social media has also been increasingly used as a novel source of knowledgebase for extracting timely and relevant security threats, which are fed to the threat intelligence systems for better performance. However, with possible campaigns spreading false security threats, these systems can become vulnerable to poisoning attacks. In this work, we proposed novel approaches for detecting misinformation about cybersecurity and privacy threats on social media, focusing on two topics with different types of misinformation: phishing websites and Zoom's security & privacy threats. We developed a framework for detecting inaccurate phishing claims on Twitter. Using this framework, we could label about 9% of URLs and 22% of phishing reports as misinformation. We also proposed another framework for detecting misinformation related to Zoom's security and privacy threats on multiple platforms. Our classifiers showed great performance with more than 98% accuracy. Employing these classifiers on the posts from Facebook, Instagram, Reddit, and Twitter, we found respectively that about 18%, 3%, 4%, and 3% of posts were misinformation. In addition, we studied the characteristics of misinformation posts, their authors, and their timelines, which helped us identify campaigns.