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

Celia Chen, Alex Leitch, William Jordan Conway et al.

The quality of a user's social media experience is determined both by the content they see and by the quality of the conversation and interaction around it. In this paper, we look at replies to tweets from mainstream media outlets and official government agencies and assess if they are good faith, engaging honestly and constructively with the original post, or bad faith, attacking the author or derailing the conversation. We assess automated approaches that may help in making this determination and then show that within our dataset of replies to mainstream media outlets and government agencies, bad faith interactions constitute 68.3% of all replies we studied, suggesting potential concerns about the quality of discourse in these specific conversational contexts. This is particularly true from verified accounts, where 91.7% of replies were bad faith. Given that verified accounts are algorithmically amplified, we discuss the implications of our work for understanding the user experience on social media.

Nils Schwager, Simon Münker, Alistair Plum et al.

The transition of Large Language Models (LLMs) from exploratory tools to active "silicon subjects" in social science lacks extensive validation of operational validity. This study introduces Conditioned Comment Prediction (CCP), a task in which a model predicts how a user would comment on a given stimulus by comparing generated outputs with authentic digital traces. This framework enables a rigorous evaluation of current LLM capabilities with respect to the simulation of social media user behavior. We evaluated open-weight 8B models (Llama3.1, Qwen3, Ministral) in English, German, and Luxembourgish language scenarios. By systematically comparing prompting strategies (explicit vs. implicit) and the impact of Supervised Fine-Tuning (SFT), we identify a critical form vs. content decoupling in low-resource settings: while SFT aligns the surface structure of the text output (length and syntax), it degrades semantic grounding. Furthermore, we demonstrate that explicit conditioning (generated biographies) becomes redundant under fine-tuning, as models successfully perform latent inference directly from behavioral histories. Our findings challenge current "naive prompting" paradigms and offer operational guidelines prioritizing authentic behavioral traces over descriptive personas for high-fidelity simulation.

Jinyu Cai, Yusei Ishimizu, Mingyue Zhang et al.

Social media platforms frequently impose restrictive policies to moderate user content, prompting the emergence of creative evasion language strategies. This paper presents a multi-agent framework based on Large Language Models (LLMs) to simulate the iterative evolution of language strategies under regulatory constraints. In this framework, participant agents, as social media users, continuously evolve their language expression, while supervisory agents emulate platform-level regulation by assessing policy violations. To achieve a more faithful simulation, we employ a dual design of language strategies (constraint and expression) to differentiate conflicting goals and utilize an LLM-driven GA (Genetic Algorithm) for the selection, mutation, and crossover of language strategies. The framework is evaluated using two distinct scenarios: an abstract password game and a realistic simulated illegal pet trade scenario. Experimental results demonstrate that as the number of dialogue rounds increases, both the number of uninterrupted dialogue turns and the accuracy of information transmission improve significantly. Furthermore, a user study with 40 participants validates the real-world relevance of the generated dialogues and strategies. Moreover, ablation studies validate the importance of the GA, emphasizing its contribution to long-term adaptability and improved overall results.

Gaspard Abel, Argyris Kalogeratos, Jean-Pierre Nadal et al.

The emergence of online social platforms, such as social networks and social media, has drastically affected the way people apprehend the information flows to which they are exposed. In such platforms, various information cascades spreading among users is the main force creating complex dynamics of opinion formation, each user being characterized by their own behavior adoption mechanism. Moreover, the spread of multiple pieces of information or beliefs in a networked population is rarely uncorrelated. In this paper, we introduce the Mixture of Interacting Cascades (MIC), a model of marked multidimensional Hawkes processes with the capacity to model jointly non-trivial interaction between cascades and users. We emphasize on the interplay between information cascades and user activity, and use a mixture of temporal point processes to build a coupled user/cascade point process model. Experiments on synthetic and real data highlight the benefits of this approach and demonstrate that MIC achieves superior performance to existing methods in modeling the spread of information cascades. Finally, we demonstrate how MIC can provide, through its learned parameters, insightful bi-layered visualizations of real social network activity data.

K. K. Seitenov, A. Z. Saken

The article considers particular reasons for the start of a pre-trial investigation, which are associated with the participation of persons having specialized knowledge in the proceedings.By using a number of methods of cognition of the circumstances of reality, the authors identify the issues that require resolution at the intersectoral level. Among the problematic aspects that cause the violation of citizens’ rights, there is a premature start of the pre-trial investigation, which is also due to the inconsistency and unreliability of the conclusions of experts and specialists involved both before and during the pre-trial investigation.To improve the studied sphere of public relations, proposals are made on overcoming of organizational and legal shortcomings of operational investigative activities, reasons for starting a pre-trial investigation, as well as filling the gaps in the current legislation, in terms of bringing experts and specialists to administrative and criminal responsibility.

Marcus Abilio Pereira, Rogério Duarte do Pateo

Este artigo busca promover um diálogo entre a abordagem teórica e analítica de algumas das teorias pós-coloniais, e a obra político, filosófica e crítica sobre o Brasil que o xamã e ativista indígena yanomami Davi Kopenawa, representante do povo yanomami, oferece para os “Brancos”. Este trabalho se insere dentro do programa de pesquisa delineado por Santos e Menezes (2010) com o intuito de promover a construção epistemológica de uma ecologia dos saberes. Para tanto, iremos analisar o livro “A queda do céu – palavras de um xamã yanomami” produzido e escrito conjuntamente por Davi Kopenawa e pelo antropólogo Bruce Albert. Utilizaremos uma metodologia qualitativa de cunho descritivo que tem como procedimentos a pesquisa bibliográfica e documental de fonte de dados.

Juan Carlos Velasco Perdigones

Thiago Baldani Gomes De Filippo

Este artigo discorre sobre a ilegitimidade da contravenção penal de exploração de jogos de azar, à luz das teorias da proteção de bens jurídicos e do paternalismo penal, situados no contexto da proporcionalidade penal, concluindo que o tipo contravencional não foi recepcionado pela Constituição de 1988.

Ismail Hossain, Sai Puppala, Md Jahangir Alam et al.

User activities can influence their subsequent interactions with a post, generating interest in the user. Typically, users interact with posts from friends by commenting and using reaction emojis, reflecting their level of interest on social media such as Facebook, Twitter, and Reddit. Our objective is to analyze user history over time, including their posts and engagement on various topics. Additionally, we take into account the user's profile, seeking connections between their activities and social media platforms. By integrating user history, engagement, and persona, we aim to assess recommendation scores based on relevant item sharing by Hit Rate (HR) and the quality of the ranking system by Normalized Discounted Cumulative Gain (NDCG), where we achieve the highest for NeuMF 0.80 and 0.6 respectively. Our hybrid approach solves the cold-start problem when there is a new user, for new items cold-start problem will never occur, as we consider the post category values. To improve the performance of the model during cold-start we introduce collaborative filtering by looking for similar users and ranking the users based on the highest similarity scores.

Ali Khodabandeh Yalabadi, Mehdi Yazdani-Jahromi, Sina Abdidizaji et al.

The rapid and widespread dissemination of misinformation through social networks is a growing concern in today's digital age. This study focused on modeling fake news diffusion, discovering the spreading dynamics, and designing control strategies. A common approach for modeling the misinformation dynamics is SIR-based models. Our approach is an extension of a model called 'SBFC' which is a SIR-based model. This model has three states, Susceptible, Believer, and Fact-Checker. The dynamics and transition between states are based on neighbors' beliefs, hoax credibility, spreading rate, probability of verifying the news, and probability of forgetting the current state. Our contribution is to push this model to real social networks by considering different classes of agents with their characteristics. We proposed two main strategies for confronting misinformation diffusion. First, we can educate a minor class, like scholars or influencers, to improve their ability to verify the news or remember their state longer. The second strategy is adding fact-checker bots to the network to spread the facts and influence their neighbors' states. Our result shows that both of these approaches can effectively control the misinformation spread.

Laura Honegger, Stacy Dewald

Considering the disproportionate number of people in the criminal justice system with trauma histories, in conjunction with the disproportionate number of people with mental illness who have experienced trauma, examining the trauma histories of mental health court (MHC) participants is essential. However, no studies to date have explicitly examined the trauma histories of this vulnerable population. Therefore, the present study aimed to describe the lifetime prevalence of traumatic events and posttraumatic stress disorder (PTSD) diagnosis among a sample of 163 participants within a Northeastern U.S. MHC. Gender differences were also explored. Overall, about 83% of MHC participants reported any lifetime trauma, with significantly higher rates among female participants (94.2%) as compared to male participants (78.4%). Approximately half of MHC participants reported experiencing childhood maltreatment, with women being significantly more likely to have experienced physical and sexual abuse during childhood than men. Further, women had higher rates of sexual assault and intimate partner violence. The percentage of women diagnosed with PTSD was about twice that of the men. These findings underscore the need for a trauma-informed and gender responsive approach to MHCs. Suggestions for MHCs to consider are offered, including trauma screening tools into MHC assessment procedures, cultivating a more trauma-informed culture by adapting key principles, and incorporating trauma-specific programming and therapies into their offerings.

Anette Storgaard

Matthew S. Johnston, Rosemary Ricciardelli, Maryam Ghodrati et al.

Abstract Background Mental health frameworks, best practices, and the well-being of public safety personnel in Canada are topics of increasing interest to both researchers and organizations. To protect and improve worker mental health, different training programs have been implemented to serve this population. The Road to Mental Readiness (R2MR) training regimen is one such program specialized to build cultural awareness of mental health, reduce stigma, and mitigate the cumulative impacts of exposures to potentially psychologically traumatic events among public safety personnel. However, limited research has been conducted to evaluate the effectiveness of R2MR, especially among correctional workers. Methods The current study analyzed 307 open-ended survey responses to four (4) questions about R2MR garnered from 124 Canadian provincial and territorial correctional workers between 2018–2020 to reveal their understandings and perceptions of R2MR training, and to identify what learned skills they found challenging or easy to implement. Results The results suggest that R2MR training plays a significant role in decreasing stigma and increasing mental health awareness. Across jurisdictions, R2MR creates a supportive space for open dialogue around mental health meant to shift cultural and individual barriers that often hinder treatment-seeking. Some respondents also indicated that R2MR was a starting point for intervention. Conclusions Further research is necessary to understand how R2MR and other programs could support the mental health and well-being of correctional workers.

BAHRAM NIKBAKHSH

The present study is a quantitative and survey research that has examined the relationship between physical activity, social isolation and depression among the elderly during the Covid-19 epidemic. The statistical population of the elderly (60 years and older) is in Ahvaz city, where 384 people were selected by simple random sampling. Also, the collected data were analytically analyzed using descriptive statistics and tests such as simple regression, correlation coefficients and path analysis using structural equation tests in the form of pls-smart3 and spss software. Based on the background and purpose of the study, it was found that there is no significant relationship between more physical activity and less depression in the elderly during the outbreak of Covid-19 disease. Also, more social isolation leads to more depression. For the method, the Physical Activity Scale for the Elderly, the Depression Scale for the Elderly, and the Promis social Isolation Scale were used. In this regard, path analysis was performed to assess the relationship between physical activity, social isolation, and depression. The results showed that out of 384 surveys conducted, according to the theoretical model of the research, higher social isolation had the highest impact factor on depression in the elderly (0.408). It was also found that the relationship between variables such as age and education with social isolation was not confirmed.

Hossein B. Jond

A social network population engages in collective actions as a direct result of forming a particular opinion. The strategic interactions among the individuals acting independently and selfishly naturally portray a noncooperative game. Nash equilibrium allows for self-enforcing strategic interactions between selfish and self-interested individuals. This paper presents a differential game approach to the opinion formation problem in social networks to investigate the evolution of opinions as a result of a Nash equilibrium. The opinion of each individual is described by a differential equation, which is the continuous-time Hegselmann-Krause model for opinion dynamics with a time delay in input. The objective of each individual is to seek optimal strategies for her own opinion evolution by minimizing an individual cost function. Two differential game problems emerge, one for a population that is not stubborn and another for a population that is stubborn. The open-loop Nash equilibrium actions and their associated opinion trajectories are derived for both differential games using Pontryagin's principle. Additionally, the receding horizon control scheme is used to practice feedback strategies where the information flow is restricted by fixed and complete social graphs as well as the second neighborhood concept. The game strategies were executed on the well-known Zachary's Karate Club social network. The resulting opinion trajectories associated with the game strategies showed consensus, polarization, and disagreement in final opinions.

Bianca Fileborn, Elena Cama, Alison Young

Rideshare and taxi services may commonly be perceived as safer modes of travel, particularly in comparison to public transport, and the introduction of rideshare services such as Uber has transformed urban mobilities. Yet, there is emerging anecdotal evidence to suggest that both taxi and rideshare services are sites of sexual harassment and violence. However, little is known about passengers’ perceptions of safety when using taxis and rideshare services, an issue with significant implications for mobility, civic participation and social inclusion. To address this gap, we explore findings from an online survey and one-on-one interviews with rideshare and taxi patrons to examine their perceptions of safety when using taxi and rideshare services and the factors that facilitate or impede feelings of safety, including the influence of the COVID-19 pandemic. In closing, we consider the implications of the findings for conceptualisations of safety, developing policy and practice, and future research.

Piero Grasso

Nell’articolo l’autore ripercorre la sua esperienza di partecipazione alla “Nave della legalità” prima in qualità di Procuratore Nazionale Antimafia, poi come Presidente del Senato e, infine, come Senatore. Tracciandone un racconto personale, l’autore offre un affresco emotivo e civico del viaggio da Civitavecchia a Palermo, mettendo in luce l’entusiasmo e il coinvolgimento degli studenti e delle studentesse presenti. 

Joanne G. Patterson, Tia N. Borger, Jessica L. Burris et al.

Ana Elizabete Mota, Ricardo Lara

É oportuna, pertinente e absolutamente necessária a temática que o leitor tem em mãos neste número da Katalysis. Ao abordar a desigualdade e a fome como fenômenos inerentes ao desenvolvimento do capitalismo, perquire as singularidades da atual conjuntura brasileira, identificando suas determinações históricas no âmbito da relação dialética e contraditória entre crescimento da riqueza e a pauperização, processos que a crise capitalista, e no seu interior, a crise sanitária, tornaram mais agudo, derruindo conquistas civilizatórias.

Bhavtosh Rath, Wei Gao, Jaideep Srivastava

The plague of false information, popularly called fake news has affected lives of news consumers ever since the prevalence of social media. Thus understanding the spread of false information in social networks has gained a lot of attention in the literature. While most proposed models do content analysis of the information, no much work has been done by exploring the community structures that also play an important role in determining how people get exposed to it. In this paper we base our idea on Computational Trust in social networks to propose a novel Community Health Assessment model against fake news. Based on the concepts of neighbor, boundary and core nodes of a community, we propose novel evaluation metrics to quantify the vulnerability of nodes (individual-level) and communities (group-level) to spreading false information. Our model hypothesizes that if the boundary nodes trust the neighbor nodes of a community who are spreaders, the densely-connected core nodes of the community are highly likely to become spreaders. We test our model with communities generated using three popular community detection algorithms based on two new datasets of information spreading networks collected from Twitter. Our experimental results show that the proposed metrics perform clearly better on the networks spreading false information than on those spreading true ones, indicating our community health assessment model is effective.