Diffusion of information, innovation, and ideas is an important phenomenon in social networks. Information propagates through the network and reaches from one person to the next. In many settings, it is meaningful to restrict diffusion so that each node can spread information to only a limited number of its neighbors rather than to all of them. Such social networks are called closed social networks. In recent years, social media platforms have emerged as an effective medium for commercial entities, where the objective is to maximize profit. In this paper, we study the Profit Maximization in Closed Social Networks (PMCSN) problem in the context of viral marketing. The input to the problem is a closed social network and two positive integers $\ell$ and $B$. The problem asks to select seed nodes within a given budget $B$; during the diffusion process, each node is restricted to choose at most $\ell$ outgoing links for information diffusion; and the objective is to maximize the profit earned by the seed set. The PMCSN problem generalizes the Influence Maximization problem, which is NP-hard. We propose two solution approaches for PMCSN: a sampling-based approximate solution and a marginal-gain-based heuristic solution. We analyze the sample complexity, running time, and space requirements of the proposed approaches. We conduct experiments on real-world, publicly available social network datasets. The results show that the seed sets and diffusion links chosen by our methods yield higher profit than baseline methods. The implementation and data are available at \texttt{https://github.com/PoonamSharma-PY/ClosedNetwork}.
Con la reforma del Código civil español de 2021 en materia de apoyo de personas con discapacidad, el legislador pretendió cambiar el paradigma en el trato jurídico de estas personas, y con especial énfasis en lo que se refiere a su capacidad para actuar en el tráfico jurídico. Naturalmente, ello incide en la regulación de la capacidad contractual de las personas con discapacidad, que, según pretensión del legislador de 2021 expresada en el preámbulo de la Ley 8/2021, se quiere que sea igual a la de las personas sin discapacidad. Lo que se pretende ver en este trabajo es si, con la regulación actual tras 2021 y en la propuesta de modernización del Código civil en materia de obligaciones y contratos de 2023, ese desiderátum del legislador se ha cumplido o, en realidad, las personas con discapacidad afectante a su aptitud volitiva y cognitiva siguen teniendo limitaciones en su capacidad para contratar.
Background: The conflict in the Papua Mountains is a strategic national issue involving political, security, social, and human rights aspects. During Joko Widodo's administration from 2019 to 2024, Papua has been one of the national development priorities, but various reports indicate that violence and human rights violations against civilians continue to occur.
Aims: This study aims to analyze the implementation of human rights principles in government policies related to conflict management in the Papua Mountains during Joko Widodo's administration from 2019 to 2024, as well as to identify the extent to which these policies are consistent with the principles of justice and conflict resolution.
Methods: This research uses a qualitative approach with a normative legal research method. Data was collected through a literature review of legislation, policy documents, reports from national and international human rights institutions, and relevant academic literature. The analysis was conducted using a descriptive-qualitative method by comparing legal norms and human rights principles with policy practices in the field.
Results: The results of the study indicate that the government has issued several important policies, namely the establishment of the Papua Pegunungan Province, the deployment of the Indonesian National Armed Forces (TNI) and the Indonesian National Police (Polri), the implementation of Limited Military Operations, and the acceleration of infrastructure and socio-economic development. These policies have contributed to security stability and improved community welfare. However, their implementation has raised various issues, including human rights violations against civilians, forced displacement, and regional development disparities.
Conclusion: Conflict management in Papua Pegunungan during the 2019–2024 period demonstrates the state's commitment to ensuring security and development, but the implementation of human rights principles remains partial. A more humane, participatory, and equitable approach is needed to achieve sustainable conflict resolution in accordance with human rights principles and social justice
Diego Fonseca Mascarenhas, Alberto de Moraes Papaléo Paes, Laurimar de Matos Farias
et al.
Objective: to analyze the potentialities and challenges of developing the Policy for Minimum Price Guarantees for Sociobiodiversity Products (PGPM-Bio) within the context of the State Plan for Bioeconomy of Pará (PlanBio). Theoretical approach: from the perspective of Amartya Sen and his work Development as freedom, the study seeks to examine how PGPM-Bio establishes minimum prices for extractivist products and fosters sustainable development in the region. Method: the research employs a qualitative methodology based on the triangulation of data from national and state legislation related to the bioeconomy, as well as socioeconomic and demographic data analyzed through the lens of Amartya Sen’s capabilities theory. Data analysis was conducted using three main constructs emerging from the literature: public policies, bioeconomy, and minimum prices. Results: the main evidence indicates that the minimum price policy positively impacts the income of extractivist producers and traditional communities, contributing to the conservation of sociobiodiversity and sustainable development in the state of Pará. However, challenges are also anticipated, such as the need for more robust financial resources and policy enhancements to ensure effective implementation. The findings suggest that PGPM-Bio, by guaranteeing minimum prices for extractivist products, contributes to improving the income and quality of life of extractivists, promoting food security and economic inclusion. Conclusions: this research will contribute to the development of more effective public policies and the strengthening of the bioeconomy in the region, fostering social inclusion and environmental conservation.
Hereditary diseases can affect patients and their biological relatives, who may be at risk of developing these conditions or transmitting them to their descendants. This study explores the attitudes of a sample of Portuguese people towards receiving information about genetic risks and policies on the disclosure of such risks. An online survey using 5-point Likert scale statements (from 1 – “totally disagree” to 5 – “totally agree”) was distributed through social media and in public places, resulting in a sample of 1034 respondents with a mean (M) age of 38.58 (standard-deviation, SD = 14.91) years old; 75.4% were women, 74.4% had higher education, and 55.5% were childless. The main findings suggest that participants strongly prefer to be informed about genetic risks by a doctor rather than not being informed at all (M = 4.75; SD = 0.67), are less supportive of learning of genetic risks first by a close relative (M = 3.94; SD = 1.11), favor legislation allowing healthcare professionals to contact them even if their relatives do not wish to disclose the information (M = 4.47; SD = 0.87), and are less favorable towards laws requiring individuals to inform their direct family members of their genetic risks (M = 3.88; SD = 1.27). These findings could inform ongoing discussions about the roles and responsibilities of healthcare professionals in conveying relevant information to at-risk relatives.
Understanding how emotions diffuse through social networks is central to computational social science. Recently, large language models (LLMs) have been increasingly used to simulate social media interactions, raising the question of whether LLM-generated data can realistically reproduce emotion diffusion patterns observed in real online communities. In this study, we conduct a systematic comparison between emotion diffusion in real-world social graphs and in LLM-simulated interaction networks. We construct diffusion graphs from Reddit discussion data and compare them with synthetic social graphs generated through LLM-driven conversational simulations. Emotion states are inferred using established sentiment analysis pipelines, and both real and simulated graphs are analyzed from structural, behavioral, and predictive perspectives. Our results reveal substantial structural and dynamic discrepancies between real and simulated diffusion processes. Real-world emotion diffusion exhibits dense connectivity, repeated interactions, sentiment shifts, and emergent community structures, whereas LLM-simulated graphs largely consist of isolated linear chains with monotonic emotional trajectories. These structural limitations significantly affect downstream tasks such as graph-based emotion prediction, leading to reduced emotional diversity and class imbalance in simulated settings. Our findings highlight current limitations of LLM-based social simulation in capturing the interactive complexity and emotional heterogeneity of real social networks. This work provides empirical evidence for the cautious use of LLM-generated data in social science research and suggests directions for improving future simulation frameworks.
This paper introduces SCRAG, a prediction framework inspired by social computing, designed to forecast community responses to real or hypothetical social media posts. SCRAG can be used by public relations specialists (e.g., to craft messaging in ways that avoid unintended misinterpretations) or public figures and influencers (e.g., to anticipate social responses), among other applications related to public sentiment prediction, crisis management, and social what-if analysis. While large language models (LLMs) have achieved remarkable success in generating coherent and contextually rich text, their reliance on static training data and susceptibility to hallucinations limit their effectiveness at response forecasting in dynamic social media environments. SCRAG overcomes these challenges by integrating LLMs with a Retrieval-Augmented Generation (RAG) technique rooted in social computing. Specifically, our framework retrieves (i) historical responses from the target community to capture their ideological, semantic, and emotional makeup, and (ii) external knowledge from sources such as news articles to inject time-sensitive context. This information is then jointly used to forecast the responses of the target community to new posts or narratives. Extensive experiments across six scenarios on the X platform (formerly Twitter), tested with various embedding models and LLMs, demonstrate over 10% improvements on average in key evaluation metrics. A concrete example further shows its effectiveness in capturing diverse ideologies and nuances. Our work provides a social computing tool for applications where accurate and concrete insights into community responses are crucial.
This paper aims to analyse the implications of the development and use of artificial intelligence from both legal and social perspectives, in a context where contemporary society is deeply shaped by digitalization. Beyond the undeniable benefits brought by this emerging technology, a critical reflection is required on how national legislation can—and must—adapt to new technological realities. The study raises a fundamental question: to what extent can technological evolution be pursued without compromising core human values? In this regard, the analysis emphasizes the imperative need for balanced regulation that ensures the protection of fundamental rights while also supporting responsible innovation.
This report examines the detrimental impact of recent anti-Diversity, Equity, and Inclusion (DEI) legislation on LGBTQ+ high school and college students across the United States. Following the termination of DEI programs under an executive order in 2025, states continued to pass anti-DEI bills, significantly affecting access to gender-affirming care, inclusive education, and campus resources. National surveys of LGBTQ+ youth indicate increased mental health challenges, suicidal ideation, and enacted stigma as this wave of exclusionary policies moves forward. Additionally, educational environments have become restrictive, leading to diminished support services and increased feelings of isolation among students. The researchers explored how experiences of social stigma have changed over time, particularly before and after the implementation of anti-DEI and antitrans policies. Comparisons were made between results of surveys conducted in 2023 and 2025 with convenience samples of LGBTQ+ students at a southeastern university. The 2023 survey gave insight into their experiences with stigma in secondary school; the 2025 survey focused on stigma experiences in college. Results show stigma experience changing with increased positive connections in college compared to high school. Overall, the study highlights the importance of advocacy and inclusive policies in safeguarding the well-being of marginalized populations in higher education.
This research article examines women's experiences residing in the high-range areas of the Idukki district in Kerala, focusing on their transition from invisibility to visibility. The study was conducted among women in these regions, identifying five key informants. Data were collected through in-depth interviews, revealing a progressive change in rural women's socio-economic, political, and familial spheres over the past decade. The findings indicate that these women have become more visible in various domains of society. Financial independence has significantly enhanced their self-worth, critical in contexts with skewed gender equality. Government initiatives, such as women-specific programs and social legislation, have positively impacted women's empowerment by providing financial security. This paper identifies the underlying factors contributing to the increased visibility of rural women in political, economic, social, and cultural spheres and the gradual development of their self-worth. Additionally, it discusses the role of social work in further empowering women's visibility.
Social pathology. Social and public welfare. Criminology
Justificación: El femicidio es un delito pluriofensivo, que además del daño directo, afecta al entorno familiar y social; la muerte violenta de mujeres constituye la forma más extrema de violencia contra la mujer.
Objetivo: Estudiar las características de las mujeres sometidas a autopsia medicolegal, cuya manera de muerte se registró como homicida o pendiente de investigación policial.
Metodología: Estudio descriptivo, retrospectivo del registro de autopsias realizadas en las oficinas forenses de Tegucigalpa, San Pedro Sula y la Ceiba, durante los años 2022 y 2023. Se seleccionaron los registros pertenecientes al sexo femenino de 14 o más años de edad y cuya manera de muerte fue clasificada como homicida o pendiente de investigación policial.
Resultados: Se analizaron 574 registros de mujeres, de las cuales 386 (67%) tenían manera de muerte homicida y 188 (33%) fueron clasificadas como pendiente de investigación policial. El 61,6% de las víctimas tenían menos de 40 años, con una media de edad de 36 años, los instrumentos de lesión más utilizados fueron las armas de fuego (43%), las armas blancas (11%). El 61,6% de las víctimas tenían menos de 40 años, el 41% no superaron la secundaria.
Conclusión: El análisis del registro de mujeres autopsiadas cuya manera de muerte fue categorizada como homicida o pendiente de investigación policial, muestra un perfil caracterizado por ser mujeres jóvenes (Edad media de 36 años), de baja escolaridad, desempleadas o subempleadas, del área urbana y que fueron agredidas principalmente con armas de fuego y arma blanca.
IntroductionIn Spain, legislation protecting women during the menopausal transition and postmenopause is still in its early stages. For public policies to be effective, it is essential that their design, implementation, and evaluation actively involve women going through this stage. Only from their experience and perspective can the impact of measures be maximized and ensure that they truly respond to their needs and realities. The goal of this article is to identify and analyze proposals for action that public organizations in Spain could undertake to improve the management of and transition through menopause. On the basis of the initiatives identified through women's narratives, this study aims to establish a solid basis for the inclusion of future governmental policies and practices in Spain. Adapting to the economic conditions and sociocultural aspects specific to each region can stimulate reflection and debate on their policies regarding menopause.MethodsThis qualitative study, which was conducted in Spain, was based on 20 semistructured interviews with women who had experienced physiological and symptomatic menopause in the last five years, were postmenopausal, and were actively employed. The interviews were audio-recorded, transcribed, and analyzed following an inductive thematic analysis.ResultsThe stories of the interviewees indicate three categories of government action comprising a set of specific measures. More specifically, the categories relate to: (a) proposals for accompaniment and social awareness, (b) educational and training proposals, and (c) political and regulatory proposals.ConclusionsThis study identifies governmental proposals and specific actions to improve support for the menopausal transition and postmenopause in Spain. While its findings may be applicable to other countries, further research is needed to explore how they could be adapted to the different socioeconomic and cultural realities of those contexts. Ultimately, the proposals presented lay the groundwork for developing public policies and laws that respond to the needs of women, improving their well-being and promoting gender equity in public health.
Generics (unquantified generalizations) are thought to be pervasive in communication and when they are about social groups, this may offend and polarize people because generics gloss over variations between individuals. Generics about social groups might be particularly common on Twitter (X). This remains unexplored, however. Using machine learning (ML) techniques, we therefore developed an automatic classifier for social generics, applied it to more than a million tweets about people, and analyzed the tweets. We found that most tweets (78%) about people contained no generics. However, tweets with social generics received more 'likes' and retweets. Furthermore, while recent psychological research may lead to the prediction that tweets with generics about political groups are more common than tweets with generics about ethnic groups, we found the opposite. However, consistent with recent claims that political animosity is less constrained by social norms than animosity against gender and ethnic groups, negative tweets with generics about political groups were significantly more prevalent and retweeted than negative tweets about ethnic groups. Our study provides the first ML-based insights into the use and impact of social generics on Twitter.
To navigate safely and efficiently in crowded spaces, robots should not only perceive the current state of the environment but also anticipate future human movements. In this paper, we propose a reinforcement learning architecture, namely Falcon, to tackle socially-aware navigation by explicitly predicting human trajectories and penalizing actions that block future human paths. To facilitate realistic evaluation, we introduce a novel SocialNav benchmark containing two new datasets, Social-HM3D and Social-MP3D. This benchmark offers large-scale photo-realistic indoor scenes populated with a reasonable amount of human agents based on scene area size, incorporating natural human movements and trajectory patterns. We conduct a detailed experimental analysis with the state-of-the-art learning-based method and two classic rule-based path-planning algorithms on the new benchmark. The results demonstrate the importance of future prediction and our method achieves the best task success rate of 55% while maintaining about 90% personal space compliance. We will release our code and datasets. Videos of demonstrations can be viewed at https://zeying-gong.github.io/projects/falcon/ .
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.
Gender gaps persist in the 21st century, in many aspects of society and in many types of organisation. There are earnings gaps in almost all domains, reports of glass ceilings and the “missing middle” in business, finance, law and politics, and dramatic under-representation of women in many branches of science, even in the most “gender equal” countries. This is despite decades of effort to address them, including targeted legislation and many Diversity and Inclusion initiatives. Early essentialist, competence-based explanations for the existence of gender gaps have been largely discredited at the research level, although their persistence in the public consciousness and at the level of education and training can still negatively bias both individual self-belief and organisational processes. Contemporary essentialist explanations are now emerging, with claims that such gaps are the manifestations of the presence or absence of endogenous, brain-based characteristics underpinning career progression or career preferences. The focus remains on the individual as the source of gender imbalances. Less attention has been paid to the contextual aspects of organisations where gender gaps are evident, to inclusion (or the lack of it), or the availability of unbiased reward and progression pathways. Advances in 21st century social cognitive neuroscience are revealing the importance of external organisational processes as powerful brain-changing forces, with their potentially negative impact on self-belief and a sense of belonging. Key research is demonstrating the cortical and behavioural consequences of negative social experiences, with the activation of core inhibitory pathways associated with low self-esteem, lack of engagement, and eventual withdrawal. This paper will argue that reference to such research will provide better explanations for the persistence of gender gaps, and offer evidence-based insights into addressing gender gap issues. Importantly, this is not a rejection of an endogenous, brain-based explanation for gender gaps but the elaboration of a better-informed 21st century model, flagging up the need to take factors such as cultural stereotyping and organisational bias into account in any drive toward true gender equity, or genuinely levelled playing fields.
It has been proven that labour relations are a legal relationship between an employer and an employee, which is established on a voluntary basis with regard to the use by the former (i.e., the employer) of the latter’s (i.e., the employee’s) ability to work and is expressed in mutual rights and obligations. It has been noted that in order for legal regulation to be fair, effective and appropriate, it should be based on a number of principles which determine the key priorities and vectors of legal regulation. To a large extent, the principles ensure the unity and integrity of the legal system and the legal regulation mechanism.
An emphasis is placed on the fact that certain categories of employees are employees for whom the current legislation, due to their physiological and social (including professional) properties (characteristics, signs, traits), provides for additional guarantees and/or benefits, some other advantages in working conditions compared to ordinary employees, and in some cases, increased requirements for their responsibility.
It has been generalised that the application of the principle of unity and differentiation in the legal regulation of the implementation of the right to work in certain categories of employees is a prerequisite for unimpeded access and inclusion of persons with certain specific physiological and/or social traits considered to be legally significant into the common legal space within which relations on the use of hired labour arise, develop, change and terminate.
It has been noted that the unity of legal regulation ensures a non-discriminatory approach to providing different individuals with the opportunity to realise their abilities and capacity to work through the conclusion of an employment contract. In turn, the differentiation of legal regulation allows taking into account the specific features of these employees and providing them with fair working conditions and adequate protection in accordance with their capabilities and needs due to these features.
Law in general. Comparative and uniform law. Jurisprudence
This review explored the potential of edible insects to address the challenges of malnutrition and food security. Although grain production in China has met the Food and Agriculture Organization standards, the shortage of protein supply is still a big issue. Moreover, expanding livestock farming is considered unsustainable and environmentally unfriendly. Edible insects have become an alternative with higher sustainable and ecological properties. There are 324 species of insects currently consumed in China, and they have high nutritional value, with a rich source of protein and unsaturated fatty acids. Insect farming provides numerous benefits, including green feeds for livestock, poultry, and aquaculture, sustainable organic waste management, as well as industrial and pharmaceutical raw materials. The food toxicological evaluations conducted in China indicated that edible insects are safe for general consumption by the Chinese, but allergies and other related food safety issues should not be ignored. Consumer acceptance is another barrier to overcome, with different schemas between China and Western countries. More research on the potential functions of edible insects and their product development may enhance their acceptance in China. Overall, incorporating edible insects into our diet is a promising solution to address challenges related to protein supply and food security. To ensure safety and sustainability, appropriate legislation, quality regulations, large-scale insect farms, and acceptable processing techniques are necessary. Moreover, more scientific research and social awareness are required to promote the culture and utilization of edible insects in China.
Nutrition. Foods and food supply, Food processing and manufacture
Radujević Katarina, Bogavac-Stanojević Nataša, Nedeljković Rade
et al.
Background/Aim. Cataract surgery is one of the most often performed surgical interventions. The predominant method in Western countries is phacoemulsification, while in developing countries, the extracapsular cataract extraction (ECCE) method remains popular. The aim of the study was to evaluate the cost-effectiveness of these two cataract surgery techniques from the provider’s perspective if operation complications were the outcome of the interest. Methods. The data were obtained from the Department of Ophthalmology of the General Hospital Kruševac during a one-year period. A total of 1,179 surgeries by five surgeons were performed. The cost-effectiveness was evaluated using the decision tree. All probabilities were calculated based on the likelihood of the occurrence during the study period. Only direct costs were considered, and values were taken from the documentation at the hospital and the official price list of health services. One- and two-way sensitivity analyses were performed. Results. The total cost per patient in the phacoemulsification group was 71,008.70 Serbian dinars (RSD), while the total cost in the ECCE group was 74,340.36 RSD. At the same time, phacoemulsification shows higher effectiveness than the ECCE method, with 87% and 57% of patients without complications, respectively. With these results, phacoemulsification was the dominant strategy compared to ECCE. The sensitivity analysis revealed that the results are sensitive to the number of performed operations per year. Conclusion. The phacoemulsification technique seems to be the preferred technique for cataract surgery. All the investment in phacoemulsification equipment and consumables is justified if the number of surgeries per year exceeds 350.
The study investigates the role of 'superspreaders' in shaping opinions within networks, distinguishing three types: A, B, and C. Type A has a significant influence in shaping opinions, Type B acts as a counterbalance to A, and Type C functions like media, providing an objective viewpoint and potentially regulating A and B's influence. The research uses a confidence coefficient and z-score to survey superspreaders' behaviors, with a focus on the conditions affecting group dynamics and opinion formation, including environmental factors and forgetfulness over time. The findings offer insights for improving online communication security and understanding social influence. This paper is partially an attempt to utilize "Generative AI" and was written with educational intent. There are currently no plans for it to become a peer-reviewed paper.