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

Zijian Long, Haopeng Wang, Haiwei Dong et al.

The social metaverse is a growing digital ecosystem that blends virtual and physical worlds. It allows users to interact socially, work, shop, and enjoy entertainment. However, privacy remains a major challenge, as immersive interactions require continuous collection of biometric and behavioral data. At the same time, ensuring high-quality, low-latency streaming is difficult due to the demands of real-time interaction, immersive rendering, and bandwidth optimization. To address these issues, we propose ASMS (Adaptive Social Metaverse Streaming), a novel streaming system based on Federated Multi-Agent Proximal Policy Optimization (F-MAPPO). ASMS leverages F-MAPPO, which integrates federated learning (FL) and deep reinforcement learning (DRL) to dynamically adjust streaming bit rates while preserving user privacy. Experimental results show that ASMS improves user experience by at least 14% compared to existing streaming methods across various network conditions. Therefore, ASMS enhances the social metaverse experience by providing seamless and immersive streaming, even in dynamic and resource-constrained networks, while ensuring that sensitive user data remains on local devices.

Michael D. Ekstrand, Afsaneh Razi, Aleksandra Sarcevic et al.

Recommender systems are usually designed by engineers, researchers, designers, and other members of development teams. These systems are then evaluated based on goals set by the aforementioned teams and other business units of the platforms operating the recommender systems. This design approach emphasizes the designers' vision for how the system can best serve the interests of users, providers, businesses, and other stakeholders. Although designers may be well-informed about user needs through user experience and market research, they are still the arbiters of the system's design and evaluation, with other stakeholders' interests less emphasized in user-centered design and evaluation. When extended to recommender systems for social good, this approach results in systems that reflect the social objectives as envisioned by the designers and evaluated as the designers understand them. Instead, social goals and operationalizations should be developed through participatory and democratic processes that are accountable to their stakeholders. We argue that recommender systems aimed at improving social good should be designed *by* and *with*, not just *for*, the people who will experience their benefits and harms. That is, they should be designed in collaboration with their users, creators, and other stakeholders as full co-designers, not only as user study participants.

Christopher Freeman

Fraud is the most frequently experienced crime in the UK, yet significantly underreported. Despite its prevalence, understanding and addressing fraud remains challenging. This paper applies the interdisciplinary framework of ‘wicked problems’ to fraud, proposing a novel approach to categorise fraud based on its impact on victims rather than the intent of perpetrators. The article introduces new categories: Acute Impact Fraud (AIF) and Diffuse Impact Fraud (DIF). In AIF the impacts of fraud falls on an individual or a small number of victims, while DIF describes fraud affecting large entities like governments or large businesses, where the impact is shared among many, often resulting in less noticeable individual harm but significant collective loss. A third category, Hybrid Impact Fraud (HIF), is also proposed, where fraud has both acute and diffuse impacts, affecting some victims significantly while spreading minor effects across a larger group. This new approach seeks to enhance the understanding and management of fraud, emphasising victim impact over perpetrator intent, and contributing to the nascent field of economic criminology.

Chih-Chung Hsu, Chia-Ming Lee, Yu-Fan Lin et al.

Social media popularity (SMP) prediction is a complex task involving multi-modal data integration. While pre-trained vision-language models (VLMs) like CLIP have been widely adopted for this task, their effectiveness in capturing the unique characteristics of social media content remains unexplored. This paper critically examines the applicability of CLIP-based features in SMP prediction, focusing on the overlooked phenomenon of semantic inconsistency between images and text in social media posts. Through extensive analysis, we demonstrate that this inconsistency increases with post popularity, challenging the conventional use of VLM features. We provide a comprehensive investigation of semantic inconsistency across different popularity intervals and analyze the impact of VLM feature adaptation on SMP tasks. Our experiments reveal that incorporating inconsistency measures and adapted text features significantly improves model performance, achieving an SRC of 0.729 and an MAE of 1.227. These findings not only enhance SMP prediction accuracy but also provide crucial insights for developing more targeted approaches in social media analysis.

Haiko Lietz

Social Network Analysis is a way of studying agents embedded in contexts. In about 1998, physicists discovered social networks as representations of complex systems. Small-world and scale-free networks are the paradigmatic models of this Network Science. Relying on various models and mechanisms of socio-cultural processes, an identity model is developed and calibrated in a case study of Social Network Science. This research domain results from the union of Social Network Analysis and Network Science. A unique dataset of 25,760 scholarly articles from one century of research (1916-2012) is created. Clustering this set of publications, five subdomains are detected and analyzed in terms of authorship, citation, and word usage structures and dynamics. The scaling hypothesis of percolation theory is formulated for socio-cultural systems, namely that power-law size distributions like Lotka's, Bradford's, and Zipf's Law mean that the described identity resides at the phase transition between the stability and change of meaning. In this case, it can be diagnosed using bivariate scaling laws and Abbott's heuristic of fractal distinctions. Identities are not dichotomies but dualities of social network and cultural domain, micro and macro phenomena, as well as stability and change. Story sets that give direction to research fluctuate less, are less distinctive, and more inert than the individuals doing the research. Identities are scale-free. Six senses are diagnostic of different aspects of identity, and when they come together as process, a complex socio-cultural system comes into existence. A mutual benefit that results from mating Relational Sociology and Network Science is identified. The latter can learn from the former that social systems are dualities of transactions and meaning. For the social sciences, the importance of Paretian thinking (scale invariance) is pointed out.

Cayley Russell, Justine Law, Sameer Imtiaz et al.

Abstract Background An emerging public health threat of methamphetamine/opioid co-use is occurring in North America, including increases in overdoses related to concomitant methamphetamine/opioid use. This presents a potential risk to established treatments for opioid use disorder (i.e., medications for opioid use disorder [MOUD]). To date, few studies have examined the impact of methamphetamine use on MOUD-related outcomes, and no studies have synthesized data on MOUD retention. Methods A scoping review was undertaken to examine the impact of methamphetamine use on MOUD retention. All original published research articles were searched in Embase, MEDLINE, PsychINFO, CINAHL, Scopus, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews and Cochrane Protocols, and Google scholar databases. Data were extracted into a standardized data extraction chart. Findings were presented narratively. Results All eight included studies demonstrated an increased likelihood of treatment discontinuation or dropout among patients enrolled in MOUD who used methamphetamine. The frequency of methamphetamine use was also associated with MOUD dropout, in that those who used methamphetamine more often were more likely to discontinue MOUD. The definitions and measurements of MOUD retention varied considerably, as did the magnitude of effect size. Conclusions Results indicate that methamphetamine use has an undesirable impact on MOUD retention and results in an increased risk of treatment discontinuation or dropout. Strategies to identify concurrent methamphetamine use among individuals engaging in MOUD and educate them on the increased risk for dropout should be undertaken. Further research is needed to understand how MOUD retention among patients with concomitant opioid and methamphetamine use can be improved.

Katherine LeMasters, Angela Benson, Christopher Corsi et al.

Abstract Background While the severe detrimental impact of COVID-19 on incarcerated people is well known, little is known about the experience of COVID-19 on those on community supervision. Our objective was to better understand the experience of the COVID-19 pandemic and its collateral consequences for those on community supervision (e.g., probation, parole). Beginning in December 2020, we conducted 185 phone surveys about COVID-19 with participants in The Southern Pre-Exposure Prophylaxis (PrEP) Study across its three sites - Florida, Kentucky, and North Carolina. We conducted rapid assessment interviews with both closed- and open-ended questions. We calculated descriptive statistics for close-ended questions and conducted a content analysis for open-ended questions. Results The COVID-19 pandemic affected those on community supervision through their experiences in the community and while incarcerated with over one-quarter of participants being reincarcerated during this time. In addition to many (128/185) experiencing COVID-19 symptoms, about half (85/185) of participants reported a diagnosis in their network with 16 of those participants losing loved ones to the pandemic. Participants experienced disruptions to their social network, healthcare, and livelihoods. Though many maintained their support systems, others felt isolated and depressed. Experiences during COVID-19 exacerbated difficulties already faced by those with criminal involvement. Conclusions The public health community must recognize those experiencing probation and parole, not only those housed in carceral facilities, as disproportionately impacted by the COVID-19 pandemic. We must tailor programs and services to meet their needs.

Karolis Zilius, Tasos Spiliotopoulos, Aad van Moorsel

The rise in adoption of cryptoassets has brought many new and inexperienced investors in the cryptocurrency space. These investors can be disproportionally influenced by information they receive online, and particularly from social media. This paper presents a dataset of crypto-related bounty events and the users that participate in them. These events coordinate social media campaigns to create artificial "hype" around a crypto project in order to influence the price of its token. The dataset consists of information about 15.8K cross-media bounty events, 185K participants, 10M forum comments and 82M social media URLs collected from the Bounties(Altcoins) subforum of the BitcoinTalk online forum from May 2014 to December 2022. We describe the data collection and the data processing methods employed and we present a basic characterization of the dataset. Furthermore, we discuss potential research opportunities afforded by the dataset across many disciplines and we highlight potential novel insights into how the cryptocurrency industry operates and how it interacts with its audience.

Nabeel Gillani, Rebecca Eynon

Over the past decade, an explosion in the availability of education-related datasets has enabled new computational research in education. Much of this work has investigated digital traces of online learners in order to better understand and optimize their cognitive learning processes. Yet cognitive learning on digital platforms does not equal education. Instead, education is an inherently social, cultural, economic, and political process manifesting in physical spaces, and educational outcomes are influenced by many factors that precede and shape the cognitive learning process. Many of these are social factors like children's connections to schools (including teachers, counselors, and role models), parents and families, and the broader neighborhoods in which they live. In this article, we briefly discuss recent studies of learning through large-scale digital platforms, but largely focus on those exploring sociological aspects of education. We believe computational social scientists can creatively advance this emerging research frontier-and in doing so, help facilitate more equitable educational and life outcomes.

Manith Adikari, Angelo Cangelosi, Randy Gomez

A social robot acting as a 'mediator' can enhance interactions between humans, for example, in fields such as education and healthcare. A particularly promising area of research is the use of a social robot mediator in a multiparty setting, which tends to be the most applicable in real-world scenarios. However, research in social robot mediation for multiparty interactions is still emerging and faces numerous challenges. This paper provides an overview of social robotics and mediation research by highlighting relevant literature and some of the ongoing problems. The importance of incorporating relevant psychological principles for developing social robot mediators is also presented. Additionally, the potential of implementing a Theory of Mind in a social robot mediator is explored, given how such a framework could greatly improve mediation by reading the individual and group mental states to interact effectively.

Alex Kresovich, Nora Sanzo, Whitney Brothers et al.

Introduction: Federal, state, local, and non-government officials have developed and implemented a variety of vaping prevention messages to curtail the vaping epidemic among youth in the US. This study sought to collect a comprehensive set of vaping prevention messages and characterize the themes and features of those messages. Methods: We used a two-fold search strategy to identify messages, utilizing the existing content database from Vaping Prevention Resource (vapingprevention.org) and supplementing those messages with web searches. Potential messages were included if they were vaping prevention-oriented, appropriate or relevant for youth, and in a static web or print format. Results: A total of 220 messages met criteria. Messages were coded on the presence or absence of 37 objective features within five categories: message themes, imagery, text features, message perspective, and other (e.g., source). The most common themes were nicotine addiction (32%), chemicals (30%), health effects (24%), and industry targeting (19%). Eighty-five percent of messages included imagery, with 27% showing a vaping device, 22% showing smoke or vapor, and 21% showing a person’s face. Just over half (56%) included a message source. Conclusions: Vaping prevention messages for youth have commonly focused on addiction and health risks of vaping, and they vary on a series of text and image features. Further research is needed to understand the efficacy of messaging approaches in preventing vaping among youth.

Kazuya Kikuchi

This paper studies the allocation of voting weights in a committee representing groups of different sizes. We introduce a partial ordering of weight allocations based on stochastic comparison of social welfare. We show that when the number of groups is sufficiently large, this ordering asymptotically coincides with the total ordering induced by the cosine proportionality between the weights and the group sizes. A corollary is that a class of expectation-form objective functions, including expected welfare, the mean majority deficit and the probability of inversions, are asymptotically monotone in the cosine proportionality.

Klaus Witold

A Romanian Roma community has been present in the largest Polish cities since the beginning of the 1990s. Although their presence was initially perceived as temporary, some members of this group have now been living in Poland for more than 20 years. However, for much of that time they have been invisible to the authorities, with only occasional exposure, and the main reasons for intervention were an attempt to remove them from the country, or from territory they were living on. In this paper, I would like to describe the situation of Romanian Roma in one Polish city, Wrocław. On their example I present different levels of exclusion from the community and space, describe the process of marginalisation (as a part of anti-Roma practices), as well as the tendency to use criminal law to discipline behaviours which society considers to be inappropriate and which it does not want to see. I’m thus presenting problems of evictions from public and private spaces, cases of prejudice followed by xenophobic attacks performed by representatives of Polish society and general lack of support neither from the general public, social institutions or police. Those practices lead to dep ravation of sense of security of the Roma population in Wrocław as police officers are perceived by them (and behaves) rather as oppressors who chase beggars away, fine them and confiscate money they earned on the street. And they fail in protection Roma community against xenophobic violence form the host society – or to be more precise they decided to abdicate from this role. The control of and state’s violence against the Roma community is made possible by labelling them as non-members of society, as strangers – persons to whom we can apply different rules than to ourselves.

Wayne Jones, Ridhwana Kaoser, Benedikt Fischer

Abstract Background Into the 21st century, the conflation of high rates of chronic pain, systemic gaps in treatment availability and access, and the arrival of potent new opioid medications (e.g., slow-release oxycodone) facilitated strong increases in medical opioid dispensing in Canada. These persisted until post-2010 alongside rising opioid-related adverse (e.g., morbidity/mortality) outcomes. We examine patterns, trends and determinants of opioid dispensing in Canada, and specifically its 10 provinces, for the years 2005–2020. Methods Raw data on prescription opioid dispensing were obtained from a large national community-based pharmacy database (IQVIA/Compuscript), converted into Defined-Daily-Doses/1,000 population/day for ‘strong’ and ‘weak’ opioid categories per standard methods. Dispensing by opioid category and formulations by province/year was assessed descriptively; regression analysis was applied to examine possible segmentation of over-time strong opioid dispensing. Results All provinces reported starkly increasing strong opioid dispensing peaking 2011–2016, and subsequent marked declines. About half reported lower strong opioid dispensing in 2020 compared to 2005, with continuous inter-provincial differences of > 100 %; weak opioids also declined post-2011/12. Segmented regression suggests breakpoints for strong opioids in 2011/12 and 2015/16, coinciding with main interventions (e.g., selective opioid delisting, new prescribing guidelines) towards more restrictive opioid utilization control. Conclusions We characterized an era of marked rise and fall, while featuring stark inter-provincial heterogeneity in opioid dispensing in Canada. While little evidence for improvements in pain care outcomes exists, the starkly inverting opioid utilization have been associated with extensive population-level harms (e.g., misuse, morbidity, mortality) over-time. This national case study raises fundamental questions for opioid-related health policy and practice.

Graham Connelly

Welcome to the autumn/fall 2021 issue of SJRCC. This is the second issue of our new two issues per year (spring and autumn) format. Regular readers will have spotted that we have a new strapline - 'an international journal of group and family care experience' – to emphasise our international reach and a scope that encompasses all care experience.

Di Fu, Fares Abawi, Hugo Carneiro et al.

To enhance human-robot social interaction, it is essential for robots to process multiple social cues in a complex real-world environment. However, incongruency of input information across modalities is inevitable and could be challenging for robots to process. To tackle this challenge, our study adopted the neurorobotic paradigm of crossmodal conflict resolution to make a robot express human-like social attention. A behavioural experiment was conducted on 37 participants for the human study. We designed a round-table meeting scenario with three animated avatars to improve ecological validity. Each avatar wore a medical mask to obscure the facial cues of the nose, mouth, and jaw. The central avatar shifted its eye gaze while the peripheral avatars generated sound. Gaze direction and sound locations were either spatially congruent or incongruent. We observed that the central avatar's dynamic gaze could trigger crossmodal social attention responses. In particular, human performances are better under the congruent audio-visual condition than the incongruent condition. Our saliency prediction model was trained to detect social cues, predict audio-visual saliency, and attend selectively for the robot study. After mounting the trained model on the iCub, the robot was exposed to laboratory conditions similar to the human experiment. While the human performances were overall superior, our trained model demonstrated that it could replicate attention responses similar to humans.

Yan Xia, Ted Hsuan Yun Chen, Mikko Kivelä

Information on social media spreads through an underlying diffusion network that connects people of common interests and opinions. This diffusion network often comprises multiple layers, each capturing the spreading dynamics of a certain type of information characterized by, for example, topic, language, or attitude. Researchers have previously proposed methods to infer these underlying multilayer diffusion networks from observed spreading patterns, but little is known about how well these methods perform across the range of realistic spreading data. In this paper, we conduct an extensive series of synthetic data experiments to systematically analyze the performance of the multilayer diffusion network inference framework, under varied network structure (e.g. density, number of layers) and information diffusion settings (e.g. cascade size, layer mixing) that are designed to mimic real-world spreading on social media. Our results show extreme performance variation of the inference framework: notably, it achieves much higher accuracy when inferring a denser diffusion network, while it fails to decompose the diffusion network correctly when most cascades in the data reach a limited audience. In demonstrating the conditions under which the inference accuracy is extremely low, our paper highlights the need to carefully evaluate the applicability of the inference before running it on real data. Practically, our results serve as a reference for this evaluation, and our publicly available implementation, which outperforms previous implementations in accuracy, supports further testing under personalized settings.

Diogo Pacheco, Pik-Mai Hui, Christopher Torres-Lugo et al.

Coordinated campaigns are used to influence and manipulate social media platforms and their users, a critical challenge to the free exchange of information online. Here we introduce a general, unsupervised network-based methodology to uncover groups of accounts that are likely coordinated. The proposed method constructs coordination networks based on arbitrary behavioral traces shared among accounts. We present five case studies of influence campaigns, four of which in the diverse contexts of U.S. elections, Hong Kong protests, the Syrian civil war, and cryptocurrency manipulation. In each of these cases, we detect networks of coordinated Twitter accounts by examining their identities, images, hashtag sequences, retweets, or temporal patterns. The proposed approach proves to be broadly applicable to uncover different kinds of coordination across information warfare scenarios.

Shang-Yu Yang, Kai-Li Chen, Pin-Hsuan Lin et al.

Introduction: Inadequate sleep is common among adolescents. Females have been found to have higher sleep requirement than that in males. This study aimed at (1) investigating the associations of sleep duration with smartphone dependence and a health-promoting lifestyle, and (2) identifying predictor(s) of inadequate sleep among adolescent females. Methods: This questionnaire-based cross-sectional study recruited 385 female junior college students (mean age: 17.50 ± 3.30 years) at a single tertiary education institute in December 2014. The questionnaire comprised three parts: (1) demographic/anthropometric characteristics (i.e., age, body mass index) and habits of alcohol/tobacco consumption, (2) smartphone dependence score according to the participant's response to four questions rated with five-point Likert scale, and (3) scores on compliance with six dimensions of the health-promoting lifestyle profile (HPLP), including nutrition, health responsibility, self-actualization, interpersonal support, exercise, stress management, and total score. Correlations of the study parameters and sleep adequacy (defined as ≥7 h) were investigated. Results: The mean sleep duration of the participants was 7.35 ± 1.49 h. Logistic regression analysis demonstrated significant negative correlation between smartphone dependence and sleep duration (P < 0.01), as well as positive associations of sleep duration with the nutrition (P < 0.01), health responsibility (P < 0.05), stress management (P < 0.01) dimensions, and total score (P = 0.01) of HPLP. Stepwise regression further showed that smartphone dependence was the only significant predictor of inadequate sleep (B: −0.06; standard error: 0.02; P < 0.01). Conclusion: The results of the present study underscore the importance of promoting a healthy lifestyle including prevention of smartphone dependence in maintaining healthy sleep habits in adolescent females.

Ruggero G., Basilisco S., Scardaccione G. et al.

L’articolo, partendo dalla presentazione di una innovativa esperienza trattamentale nei confronti di sex offender attuata nella Casa Circondariale di Chieti, vuole proporre l’importanza che i percorsi di inclusione nei confronti di tali autori di reato assumono quale presupposto indiscutibile per l’attuazione di programmi trattamentali specifici. L’esperienza svolta dagli operatori del carcere di Chieti si è avvalsa anche di una collaborazione con l’Università “G. d’Annunzio” che ha evidenziato come in tali autori di reato siano presenti significative distorsioni cognitive su cui è importante intervenire al fine di ottenere il recupero della persona e la riduzione della recidiva. Vengono esposti i risultati della ricerca svolta su 24 sex offender e non che ha evidenziato una presenza più significativa di distorsioni cognitive negli autori di reati sessuali rispetto agli autori di reato non a sfondo sessuale, soprattutto a danno di vittime maggiorenni piuttosto che minorenni. Vengono analizzati modelli trattamentali applicati a livello nazionale e internazionale e indicati successivi sviluppi di ricerca al fine di proporre programmi di intervento sulla stessa popolazione detenuta nel carcere di Chieti. Résumé À partir de la présentation d’un programme novateur axé sur la réinsertion de délinquants sexuels, mis en œuvre dans la prison italienne de Chieti (Casa Circondariale), l’article souligne l’importance de l’inclusion de ces délinquants en tant que condition essentielle à la réalisation de programmes de réinsertion spécifiques. Grâce à la collaboration entre le personnel pénitentiaire et les chercheurs de l’universitéUniversité « G. d’Annunzio », cette expérience prouve que ce type de délinquants est affecté par d’importants préjugés cognitifs. C’est pourquoi, il est important de réaliser une intervention de débiaisement afin d’une meilleure réhabilitation de la personne et pour contribuer à la réduction de la récidive. Les résultats de la recherche menée auprès de 24 personnes (dont certaines sont des délinquants sexuels, d’autres non) montrent que les délinquants sexuels sont affectés plus que les autres par des préjugés cognitifs et en particulier dans le cas où leurs victimes ont plus de 18 ans. En outre, dans cet article, les auteurs analysent les modèles italiens et internationaux de traitement et enfin proposent de nouvelles activités de recherche afin d’étendre ce type de programme à la totalité de la population carcérale de la prison de Chieti. Abstract Starting from the presentation of an innovative program addressing the rehabilitation of sex offenders, implemented inside the Italian prison of Chieti (Casa Circondariale), the article proposes the importance of the inclusion of these offenders as an essential condition for the implementation of specific rehabilitation programs. Thanks to the collaboration between the prison staff and the researchers coming from the University “G. d’Annunzio”, this experience shows that such offenders are affected by significant cognitive biases. Therefore, it is important to apply a debiasing intervention to better rehabilitate the person and contribute to the reduction of recidivism. The results of the research that was carried out on 24 people (some of them are sex offenders, some others not) show that the sex offenders are affected more than the others offenders by cognitive biases, and particularly when their victims were over 18. Moreover, in this paper the authors analyse Italian and international treatment models and finally they propose new research activities in order to extend this kind of program to the entire inmate population of the prison of Chieti.