Social norm interventions are used promote prosocial behaviors by highlighting prevalent actions, but their effectiveness is often limited in heterogeneous populations where shared understandings of desirable behaviors are lacking. This study explores whether multi-agent systems can establish "virtual social norms" to encourage donation behavior. We conducted an online experiment where participants interacted with a group of agents to discuss donation behaviors. Changes in perceived social norms, conformity, donation behavior, and user experience were measured pre- and postdiscussion. Results show that multi-agent interactions effectively increased perceived social norms and donation willingness. Notably, in-group agents led to stronger perceived social norms, higher conformity, and greater donation increases compared to out-group agents. Our findings demonstrate the potential of multi-agent systems for creating social norm interventions and offer insights into leveraging social identity dynamics to promote prosocial behavior in virtual environments.
Sølvi Anne Eide Lunde, Merete Røthing, Nina Elisabeth Hjorth
Bakgrunn: Nasjonale retningsliner tilrår førehandssamtalar. For å auke kunnskapen om bruken av førehandssamtalar utforska me erfaringar med og refleksjonar om førehandssamtalar i palliativ fase hos legar i primærhelsetenesta i ein mellomstor norsk kommune. Metode: Me har nytta eit kvalitativt studiedesign med fokusgruppeintervju av fem legar. Intervjuet vart tatt opp, transkribert, anonymisert og analysert ved systematisk tekstkondensering. Resultat: Legane erfarte at rolla deira i eit palliativt pasientforløp var uklar, og dei mangla rutine for involvering i førehandssamtalar. Tre hovudtema vart identifiserte: verdien av førehandssamtalar i den palliativ fasen barrierar og tilretteleggarar for førehandssamtalar organisatoriske faktorar i palliativ fase Konklusjon: Legane i studien ønskte tidleg involvering og ei tydelegare rolle i palliative pasientforløp. Førehandssamtalar bør initierast tidleg og gjentakast regelmessig ved vendepunkt i pasientforløpet for å bli kjent med pasient og pårørande sine preferansar, tankar om situasjonen, framtida og medisinsk behandling. For å styrke legane i bruk av førehandssamtalar må opplæring i klinisk kommunikasjon samt førehandssamtalar styrkast. Det er behov for meir forsking om faktorar som kan styrke legane si rolle i bruk av førehandssamtalar i kommunehelsetenesta.
Social pathology. Social and public welfare. Criminology
Van An Nguyen, Vuong Khang Huynh, Ho Nam Duong
et al.
Research on promoting cooperation among autonomous, self-regarding agents has often focused on the bi-objective optimisation problem: minimising the total incentive cost while maximising the frequency of cooperation. However, the optimal value of social welfare under such constraints remains largely unexplored. In this work, we hypothesise that achieving maximal social welfare is not guaranteed at the minimal incentive cost required to drive agents to a desired cooperative state. To address this gap, we adopt to a single-objective approach focused on maximising social welfare, building upon foundational evolutionary game theory models that examined cost efficiency in finite populations, in both well-mixed and structured population settings. Our analytical model and agent-based simulations show how different interference strategies, including rewarding local versus global behavioural patterns, affect social welfare and dynamics of cooperation. Our results reveal a significant gap in the per-individual incentive cost between optimising for pure cost efficiency or cooperation frequency and optimising for maximal social welfare. Overall, our findings indicate that incentive design, policy, and benchmarking in multi-agent systems and human societies should prioritise welfare-centric objectives over proxy targets of cost or cooperation frequency.
Large language models (LLMs) are increasingly entrusted with high-stakes decisions that affect human welfare. However, the principles and values that guide these models when distributing scarce societal resources remain largely unexamined. To address this, we introduce the Social Welfare Function (SWF) Benchmark, a dynamic simulation environment where an LLM acts as a sovereign allocator, distributing tasks to a heterogeneous community of recipients. The benchmark is designed to create a persistent trade-off between maximizing collective efficiency (measured by Return on Investment) and ensuring distributive fairness (measured by the Gini coefficient). We evaluate 20 state-of-the-art LLMs and present the first leaderboard for social welfare allocation. Our findings reveal three key insights: (i) A model's general conversational ability, as measured by popular leaderboards, is a poor predictor of its allocation skill. (ii) Most LLMs exhibit a strong default utilitarian orientation, prioritizing group productivity at the expense of severe inequality. (iii) Allocation strategies are highly vulnerable, easily perturbed by output-length constraints and social-influence framing. These results highlight the risks of deploying current LLMs as societal decision-makers and underscore the need for specialized benchmarks and targeted alignment for AI governance.
A proper mechanism design can help federated learning (FL) to achieve good social welfare by coordinating self-interested clients through the learning process. However, existing mechanisms neglect the network effects of client participation, leading to suboptimal incentives and social welfare. This paper addresses this gap by exploring network effects in FL incentive mechanism design. We establish a theoretical model to analyze FL model performance and quantify the impact of network effects on heterogeneous client participation. Our analysis reveals the non-monotonic nature of FL network effects. To leverage such effects, we propose a model trading and sharing (MTS) framework that allows clients to obtain FL models through participation or purchase. To tackle heterogeneous clients' strategic behaviors, we further design a socially efficient model trading and sharing (SEMTS) mechanism. Our mechanism achieves social welfare maximization solely through customer payments, without additional incentive costs. Experimental results on an FL hardware prototype demonstrate up to 148.86% improvement in social welfare compared to existing mechanisms.
Traditional path-planning techniques treat humans as obstacles. This has changed since robots started to enter human environments. On modern robots, social navigation has become an important aspect of navigation systems. To use learning-based techniques to achieve social navigation, a powerful framework that is capable of representing complex functions with as few data as possible is required. In this study, we benefited from recent advances in deep learning at both global and local planning levels to achieve human-aware navigation on a simulated robot. Two distinct deep models are trained with respective objectives: one for global planning and one for local planning. These models are then employed in the simulated robot. In the end, it has been shown that our model can successfully carry out both global and local planning tasks. We have shown that our system could generate paths that successfully reach targets while avoiding obstacles with better performance compared to feed-forward neural networks.
Approximately 400,000 youth in the US are living in foster care due to experiences with abuse or neglect at home. For multiple reasons, these youth often don't receive adequate social support from those around them. Despite technology's potential, very little work has explored how these tools can provide more support to foster-involved youth. To begin to fill this gap, we worked with current and former foster-involved youth to develop the first digital tool that aims to increase social support for this population, creating a novel system in which users complete reflective check-ins in an online community setting. We then conducted a pilot study with 15 current and former foster-involved youth, comparing the effect of using the app for two weeks to two weeks of no intervention. We collected qualitative and quantitative data, which demonstrated that this type of interface can provide youth with types of social support that are often not provided by foster care services and other digital interventions. The paper details the motivation behind the app, the trauma-informed design process, and insights gained from this initial evaluation study. Finally, the paper concludes with recommendations for designing digital tools that effectively provide social support to foster-involved youth.
Sharon Fernandez, Lithin Zacharias, Harikrishnan U.
Aging is a period of decline and social attitude towards old age affects the aged population. The practice of institutionalizing the elderly is a broad spreading concept in the modern world, and the old age homes and hospices are growing day by day. The current study aims at exploring the life experiences of the elderly on account of the transition happening due to institutionalization. The current study followed the multiple case study design. The objectives of the study are 1) to understand the social conditions that propel the elderly to choose institutional care, 2) to assess changing the attitude of the elderly towards the society and 3) to determine the coping mechanisms by the elderly in institutions, towards effective adjustment. Samples were selected from the old age homes who were above the age of 65 and institutionalized for at least ten years. Four case studies focused on the current objectives, and semi-structured interview guide was used. The study found that there was some level of psychosocial issues among the elderly and need psychosocial interventions and specialized care for the elderly in the primary, secondary and tertiary levels.
Social pathology. Social and public welfare. Criminology
Since September 2023, the Digital Services Act (DSA) obliges large online platforms to submit detailed data on each moderation action they take within the European Union (EU) to the DSA Transparency Database. From its inception, this centralized database has sparked scholarly interest as an unprecedented and potentially unique trove of data on real-world online moderation. Here, we thoroughly analyze all 353.12M records submitted by the eight largest social media platforms in the EU during the first 100 days of the database. Specifically, we conduct a platform-wise comparative study of their: volume of moderation actions, grounds for decision, types of applied restrictions, types of moderated content, timeliness in undertaking and submitting moderation actions, and use of automation. Furthermore, we systematically cross-check the contents of the database with the platforms' own transparency reports. Our analyses reveal that (i) the platforms adhered only in part to the philosophy and structure of the database, (ii) the structure of the database is partially inadequate for the platforms' reporting needs, (iii) the platforms exhibited substantial differences in their moderation actions, (iv) a remarkable fraction of the database data is inconsistent, (v) the platform X (formerly Twitter) presents the most inconsistencies. Our findings have far-reaching implications for policymakers and scholars across diverse disciplines. They offer guidance for future regulations that cater to the reporting needs of online platforms in general, but also highlight opportunities to improve and refine the database itself.
Intensified preventive measures during the COVID-19 pandemic, such as lockdown and social distancing, heavily increased the perception of social isolation (i.e., a discrepancy between one's social needs and the provisions of the social environment) among young adults. Social isolation is closely associated with situational loneliness (i.e., loneliness emerging from environmental change), a risk factor for depressive symptoms. Prior research suggested vulnerable young adults are likely to seek support from an online social platform such as Reddit, a perceived comfortable environment for lonely individuals to seek mental health help through anonymous communication with a broad social network. Therefore, this study aims to identify and analyze depression-related dialogues on loneliness subreddits during the COVID-19 outbreak, with the implications on depression-related infoveillance during the pandemic. Our study utilized logistic regression and topic modeling to classify and examine depression-related discussions on loneliness subreddits before and during the pandemic. Our results showed significant increases in the volume of depression-related discussions (i.e., topics related to mental health, social interaction, family, and emotion) where challenges were reported during the pandemic. We also found a switch in dominant topics emerging from depression-related discussions on loneliness subreddits, from dating (prepandemic) to online interaction and community (pandemic), suggesting the increased expressions or need of online social support during the pandemic. The current findings suggest the potential of social media to serve as a window for monitoring public mental health. Our future study will clinically validate the current approach, which has implications for designing a surveillance system during the crisis.
José Carmona-Santiago, Marta García-Ruíz, Maria Luisa Maíquez-Chaves
et al.
Tradicionalmente el Pueblo Gitano ha encontrado en el seno familiar su mayor fortaleza para adaptarse a un medio adverso. Este estudio empírico con metodología cuantitativa explora la contribución respectiva del contexto (calidad del vecindario y apoyo social), del sistema familiar (coherencia y adaptabilidad) y del individuo (bienestar subjetivo) sobre la resiliencia de las figuras parentales desde una perspectiva psicosocial y comunitaria. Los participantes fueron 95 familias de etnia gitana residentes en las Islas Canarias y 16 técnicos del ámbito social, cuyas respuestas a los cuestionarios fueron sometidas a análisis estadísticos descriptivos y un modelo de regresión. Las familias viven en vecindarios desfavorecidos debido a su baja formación, el empleo precario y los escasos apoyos formales recabados. Las figuras parentales perciben un buen nivel de cohesión familiar y de bienestar subjetivo.El modelo de regresión sobre la resiliencia muestra la contribución negativa de la problemática social del vecindario, y la contribución positiva de los ingresos económicos estables, vivir en un barrio inclusivo, disfrutar de cohesión familiar y de bienestar subjetivo.En conclusión, las familias de etnia gitana presentan fortalezas y potencialidades que, junto con los apoyos comunitarios apropiados, garantizan una resiliencia normalizadora sobre aquellos valores familiares que permitieron su supervivencia en tiempos difíciles.
Social Sciences, Social pathology. Social and public welfare. Criminology
Humans are constantly influenced by others' behavior and opinions. Of importance, social influence among humans is shaped by reciprocity: we follow more the advice of someone who has been taking into consideration our opinions. In the current work, we investigate whether reciprocal social influence can emerge while interacting with a social humanoid robot. In a joint task, a human participant and a humanoid robot made perceptual estimates and then could overtly modify them after observing the partner's judgment. Results show that endowing the robot with the ability to express and modulate its own level of susceptibility to the human's judgments represented a double-edged sword. On the one hand, participants lost confidence in the robot's competence when the robot was following their advice; on the other hand, participants were unwilling to disclose their lack of confidence to the susceptible robot, suggesting the emergence of reciprocal mechanisms of social influence supporting human-robot collaboration.
Siddharth Barman, Anand Krishna, Pooja Kulkarni
et al.
We study the problem of allocating indivisible goods among $n$ agents with the objective of maximizing Nash social welfare (NSW). This welfare function is defined as the geometric mean of the agents' valuations and, hence, it strikes a balance between the extremes of social welfare (arithmetic mean) and egalitarian welfare (max-min value). Nash social welfare has been extensively studied in recent years for various valuation classes. In particular, a notable negative result is known when the agents' valuations are complement-free and are specified via value queries: for XOS valuations, one necessarily requires exponentially many value queries to find any sublinear (in $n$) approximation for NSW. Indeed, this lower bound implies that stronger query models are needed for finding better approximations. Towards this, we utilize demand oracles and XOS oracles; both of these query models are standard and have been used in prior work on social welfare maximization with XOS valuations. We develop the first sublinear approximation algorithm for maximizing Nash social welfare under XOS valuations, specified via demand and XOS oracles. Hence, this work breaks the $O(n)$-approximation barrier for NSW maximization under XOS valuations. We obtain this result by developing a novel connection between NSW and social welfare under a capped version of the agents' valuations. In addition to this insight, which might be of independent interest, this work relies on an intricate combination of multiple technical ideas, including the use of repeated matchings and the discrete moving knife method. In addition, we partially complement the algorithmic result by showing that, under XOS valuations, an exponential number of demand and XOS queries are necessarily required to approximate NSW within a factor of $\left(1 - \frac{1}{e}\right)$.
Chad A Melton, Olufunto A Olusanya, Nariman Ammar
et al.
The COVID-19 pandemic fueled one of the most rapid vaccine developments in history. However, misinformation spread through online social media often leads to negative vaccine sentiment and hesitancy. To investigate COVID-19 vaccine-related discussion in social media, we conducted a sentiment analysis and Latent Dirichlet Allocation topic modeling on textual data collected from 13 Reddit communities focusing on the COVID-19 vaccine from Dec 1, 2020, to May 15, 2021. Data were aggregated and analyzed by month to detect changes in any sentiment and latent topics. ty analysis suggested these communities expressed more positive sentiment than negative regarding the vaccine-related discussions and has remained static over time. Topic modeling revealed community members mainly focused on side effects rather than outlandish conspiracy theories. Covid-19 vaccine-related content from 13 subreddits show that the sentiments expressed in these communities are overall more positive than negative and have not meaningfully changed since December 2020. Keywords indicating vaccine hesitancy were detected throughout the LDA topic modeling. Public sentiment and topic modeling analysis regarding vaccines could facilitate the implementation of appropriate messaging, digital interventions, and new policies to promote vaccine confidence.
La Ley de Vagos y Maleantes (1933) constituye el primer tratamiento sistemático de la peligrosidad social en el Derecho español. Su vigencia se prolongó hasta 1970, en que fue sustituida por la Ley de Peligrosidad y Rehabilitación Social, vigente a su vez hasta 1995. Así, el concepto de peligrosidad social y sus consecuencias, las medidas de seguridad, tuvieron reconocimiento jurídico-positivo en tres regímenes políticamente incompatibles: República, dictadura franquista, democracia constitucional. Por encima de las diferencias de los sucesivos marcos normativos, la homosexualidad fue considerada paradigma de peligrosidad, y como tal fue definida, etiquetada y excluida. Cada modelo político aportó su propio argumentario ideológico, pero el resultado común fue -si es que no sigue siendo-la exclusión de un colectivo cuya única peligrosidad radicaba en el hecho de entender la autonomía sexual de modo distinto a los estereotipos hegemónicos en cada caso. Los mecanismos de disciplina y control se revistieron con ropajes jurídico-penales, pero la definición de su presupuesto nuclear -la peligrosidad-y la implementación del sistema sancionatorio -las medidas de seguridad-se asentaron siempre en principios incompatibles con los que caracterizan al Derecho penal democrático.
Law, Social pathology. Social and public welfare. Criminology
Allison M. Glasser, Joseph M. Macisco, Lauren M. Miller
et al.
Introduction: Nearly three times as many homeless youth smoke cigarettes in the United States (US) compared to the general population of youth. Few studies have focused on how to help homeless youth quit smoking. As part of a series of studies to develop a smoking cessation intervention for homeless youth, this study aimed to describe methods used in past quit attempts by homeless youth. Methods: Recruited from a drop-in center in the Midwestern US, the analytic sample was comprised of 32 unaccompanied homeless youth aged 14–24 who smoked combustible tobacco at some point in the past week. In-person qualitative interviews were conducted to understand prior quit attempt experiences of homeless youth. Results: Twenty-two youth (69%) were willing to quit smoking in the next 30 days. Most previous quit attempts were unassisted (78%). Participants frequently reported engaging in distracting behaviors (e.g., video games) or thoughts (e.g., remaining positive). Nicotine replacement therapy (NRT) was another popular method (38%), but with mostly negative reactions. While less common, vaping and use of cannabis to substitute cigarettes was reported in a notable faction of youth (28%), primarily 18–24 years of age. Conclusions: Youth are primarily engaging in non-evidence-based strategies to quit smoking. Existing evidence-based treatments are often underutilized or not used according to instructions, and youth who do use evidence-based treatments do not find them useful. Future research should explore effective cessation treatment among homeless youth that can ideally be provided at shelters and drop-in centers. Implications: Existing evidence-based treatments are underutilized by homeless youth in this study. Most homeless youth are willing to quit in the next month and are interested in trying behavioral counseling and monitored use of NRT. Drop-in centers may be an effective location from which to develop and offer targeted smoking cessation interventions for homeless youth.
Psychology, Social pathology. Social and public welfare. Criminology
Social Media can be used to extract discussion topics during a disaster. With the COVID-19 pandemic impact on South Africa, we need to understand how the law and regulation promulgated by the government in response to the pandemic contrasts with discussion topics social media users have been engaging in. In this work, we expand on traditional media analysis by using Social Media discussions driven by or directed to South African government officials. We find topics that are similar as well as different in some cases. The findings can inform further study into social media during disaster settings in South Africa and beyond. This paper sets a framework for future analysis in understanding the opinions of the public during a pandemic and how these opinions can be distilled [in a semi-automated approach] to inform government communication in the future.
Influence maximization (IM) has garnered a lot of attention in the literature owing to applications such as viral marketing and infection containment. It aims to select a small number of seed users to adopt an item such that adoption propagates to a large number of users in the network. Competitive IM focuses on the propagation of competing items in the network. Existing works on competitive IM have several limitations. (1) They fail to incorporate economic incentives in users' decision making in item adoptions. (2) Majority of the works aim to maximize the adoption of one particular item, and ignore the collective role that different items play. (3) They focus mostly on one aspect of competition -- pure competition. To address these concerns we study competitive IM under a utility-driven propagation model called UIC, and study social welfare maximization. The problem in general is not only NP-hard but also NP-hard to approximate within any constant factor. We, therefore, devise instant dependent efficient approximation algorithms for the general case as well as a $(1-1/e-ε)$-approximation algorithm for a restricted setting. Our algorithms outperform different baselines on competitive IM, both in terms of solution quality and running time on large real networks under both synthetic and real utility configurations.
Timothy P. Schofield, Nick Haslam, Peter Butterworth
AbstractPeople receiving welfare payments are stigmatized. However, previous studies of welfare recipient stereotypes have not examined whether the stigma endures after payments are no longer received and have rarely considered the stigma associated with specific categories of welfare payments. We examined whether welfare stigma endures in three experiments (total N = 873) focused on one category of welfare recipient, people receiving government income support due to their unemployment. To test if this stigmatized identity marked or scarred how people are perceived, we compared evaluations of currently unemployed benefit recipients to currently employed people who either previously received this benefit or who had no stated history of benefit receipt. Across the three experiments, we found that current recipients of unemployment benefits were evaluated as much less conscientious, less human, and poorer workers, but as somewhat more extraverted than currently employed individuals irrespective of their welfare history. Moreover, we found that currently employed individuals were evaluated similarly, regardless of whether they had a prior history of benefit receipt, and the recency of this prior benefit experience. This pattern of results suggests that receiving unemployment benefits does not scar how a person is perceived by others, but only temporarily marks how they are perceived. These findings suggest that welfare stigma may create an evaluative barrier to returning to work, but that if this barrier can be overcome there are no negative evaluations of former recipients’ character. Overall, community members seem accepting of prior benefit receipt once a person returns to work.