Dynamics Of Social Interaction Research Articles

A state-space relational event modeling approach for learning dynamic social interaction behavior

Relational event models (REMs) are the primary choice for the analysis of relational-event network data. However, the standard REM assumes static parameters, which hinders the modeling of time-varying dynamics. This assumption might be too restrictive in real-life scenarios, making a model that allows for time-varying parameters more valuable. We introduce a state-space extension of the relational event model as a way to tackle this problem. The model has three main attributes. First, it provides a statistical framework of the temporal change of the parameters. Second, it enables the forecasting of future parameter values (which can be utilized to simulate new networks that can account for temporal dynamics in out-of-sample predictions). Third, it requires smaller data structures to be loaded into computer memory compared to the standard REM; this makes the model easily scalable to large networks. We conduct empirical analyses on bike-sharing data, corporate communications, and interactions among socio-political actors to illustrate model usage and applicability.

Peer Support for Chronic Pain in Online Health Communities: Quantitative Study on the Dynamics of Social Interactions in a Chronic Pain Forum.

Peer support for chronic pain is increasingly taking place on social media via social networking communities. Several theories on the development and maintenance of chronic pain highlight how rumination, catastrophizing, and negative social interactions can contribute to poor health outcomes. However, little is known regarding the role web-based health discussions play in the development of negative versus positive health attitudes relevant to chronic pain. This study aims to investigate how participation in online peer-to-peer support communities influenced pain expressions by examining how the sentiment of user language evolved in response to peer interactions. We collected the comment histories of 199 randomly sampled Reddit (Reddit, Inc) users who were active in a popular peer-to-peer chronic pain support community over 10 years. A total of 2 separate natural language processing methods were compared to calculate the sentiment of user comments on the forum (N=73,876). We then modeled the trajectories of users' language sentiment using mixed-effects growth curve modeling and measured the degree to which users affectively synchronized with their peers using bivariate wavelet analysis. In comparison to a shuffled baseline, we found evidence that users entrained their language sentiment to match the language of community members they interacted with (t198=4.02; P<.001; Cohen d=0.40). This synchrony was most apparent in low-frequency sentiment changes unfolding over hundreds of interactions as opposed to reactionary changes occurring from comment to comment (F2,198=17.70; P<.001). We also observed a significant trend in sentiment across all users (β=-.02; P=.003), with users increasingly using more negative language as they continued to interact with the community. Notably, there was a significant interaction between affective synchrony and community tenure (β=.02; P=.02), such that greater affective synchrony was associated with negative sentiment trajectories among short-term users and positive sentiment trajectories among long-term users. Our results are consistent with the social communication model of pain, which describes how social interactions can influence the expression of pain symptoms. The difference in long-term versus short-term affective synchrony observed between community members suggests a process of emotional coregulation and social learning. Participating in health discussions on Reddit appears to be associated with both negative and positive changes in sentiment depending on how individual users interacted with their peers. Thus, in addition to characterizing the sentiment dynamics existing within online chronic pain communities, our work provides insight into the potential benefits and drawbacks of relying on support communities organized on social media platforms.

Quantitative Analysis of Causative Factors of Crime: A Case Study of District Sahiwal (Pakistan)

It is a postindustrial society in which the dynamics of social interaction and values have changed. Due to rapid technological changes, the social relations and bounding with social norms have been weakening. The impatience, delinquency, and criminal attitude of the people are increasing daily. The research objectives of this current study were to examine the causative factors of crime in district Sahiwal and to identify the elements that shape and influence criminal behavior in the region. The researcher used the quantitative method and exploited purposive sampling. The data was gathered from 120 criminals from Central Jail, Sahiwal, Pakistan. The analysis used Statistical Package for the Social Sciences (SPSS) to uncover significant patterns and relationships of variables. It was found that low socio-economic status and less academic qualification were the real causes of crime in the studied area. Based on the results, it is suggested that addressing the underlying issues of bad company, poverty, unemployment, and lack of education and strengthening legal and social frameworks can create a safer, more stable community in Sahiwal. The study's findings emphasize that only through targeted interventions that address both the symptoms and the root causes of crime can meaningful progress be made in reducing crime rates and improving the quality of life for the residents of district Sahiwal. The concerned institutions should collaborate with the concerned institutions to uplift the socio-economic status of the people, and strict law and order should be enforced to tackle deviance and crime in Sahiwal, Pakistan.

Cognitive microfoundations and social interaction dynamics. The implications of complexity for institutional theory

Cognitive microfoundations and social interaction dynamics. The implications of complexity for institutional theory

Understanding the dynamics of social interaction in SIoT: Human-machine engagement

The Social Internet of Things (SIoT) amalgamates social networks with the Internet of Things (IoT) to enable intelligent devices to form social connections analogous to human networks. This research is grounded in psychological contract theory, which examines the reciprocal mechanisms arising from diverse customer interactions to encourage user engagement and provide recommendations on social media platforms. This study in particular identifies the factors that drive customer engagement on social media. It is unique in its exploration of customer interactions within the framework of psychological contracts across multiple levels of customer engagement (through customer empowerment). The findings reveal that psychological ownership among customers is influenced by empowering interactions on social media, which ultimately drive engagement behaviors.

Breaking the silence: leveraging social interaction data to identify high-risk suicide users online using network analysis and machine learning

Suicidal thought and behavior (STB) is highly stigmatized and taboo. Prone to censorship, yet pervasive online, STB risk detection may be improved through development of uniquely insightful digital markers. Focusing on Sanctioned Suicide, an online pro-choice suicide forum, this work derived 17 egocentric network features to capture dynamics of social interaction and engagement within this uniquely uncensored community. Using network data generated from over 3.2 million unique interactions of N = 192 individuals, n = 48 of which were determined to be highest risk users (HRUs), a machine learning classification model was trained, validated, and tested to predict HRU status. Model prediction dynamics were analyzed using introspection techniques to uncover patterns in feature influence and highlight social phenomena. The model achieved a test AUC = 0.73 ([0.61, 0.85], 95% CI), suggesting that network-based socio-behavioral patterns of online interaction can signal for heightened suicide risk. Transitivity, density, and in-degree centrality were among the most important features driving this performance. Moreover, predicted HRUs tended to be targets of social exchanges with lesser frequency and possessed egocentric networks with “small world” network properties. Through the implementation of an underutilized method on an unlikely data source, findings support future incorporation of network-based social interaction features in descriptive, predictive, and preventative STB research.

Highly idealized models of scientific inquiry as conceptual systems

The social epistemology of science has adopted agent-based computer simulations as one of its core methods for investigating the dynamics of scientific inquiry. The epistemic status of these highly idealized models is currently under active debate in which they are often associated either with predictive or the argumentative functions. These two functions roughly correspond to interpreting simulations as virtual experiments or formalized thought experiments, respectively. This paper advances the argumentative account of modeling by proposing that models serve as a means to (re)conceptualize the macro-level dynamics of complex social epistemic interactions. I apply results from the epistemology of scientific modeling and the psychology of mental simulation to the ongoing debate in the social epistemology of science. Instead of considering simulation models as predictive devices, I view them as artifacts that exemplify abstract hypothetical properties of complex social epistemic processes in order to advance scientific understanding, hypothesis formation, and communication. Models need not be accurate representations to serve these purposes. They should be regarded as pragmatic cognitive tools that engender rather than replace intuitions in philosophical reasoning and argumentation. Furthermore, I aim to explain why the community tends to converge around few model templates: Since models have the potential to transform our intuitive comprehension of the subject of inquiry, successful models may literally capture the imagination of the modeling community.

Dynamics of Social Interaction, Social Support, and Psychological Well-Being in Urban Communities: Social Support Theory Perspective

This study aims to investigate the effect of Quality of Social Relationships on Social Welfare and Urban Community Quality of Life, using the Structural Equation Modeling (SEM) quantitative analysis method with the SMARTPLS tool. This research method involves collecting data from 600 samples representing various backgrounds and characteristics of individuals in an urban environment. The results showed that Quality of Social Relationships has a positive and significant influence on Social Welfare and Urban Community Quality of Life. The quality of strong and supportive social relationships is shown to play an important role in enhancing individual social welfare and improving the overall quality of life in urban communities. From the analysis using the SEM method with SMARTPLS, the findings suggest that social interaction, life satisfaction, social support, and the ability to adapt to environmental changes contribute positively to the quality of social relationships which in turn influence Social Welfare and Urban Community Quality of Life. The implication of these findings is the need to consider the importance of strengthening the quality of social relationships in developing social policies and programs aimed at improving social welfare and quality of life in urban environments.

Rebuilding Harmony: Social Interactions After the Maluku Conflict

The purpose of this study was to determine the dynamics of social interactions that were passed down from previous generations in students of the BK Study Program after the Maluku conflict. The research method used a qualitative approach with in-depth interviews with students whose families experienced the conflict in Maluku directly in 1999-2002. Through coding analysis, the research identified thematic patterns and meanings that emerged from students' narratives. Based on the results of the study, it was found that the social interaction of post-conflict Counseling students both individually and in groups can be established with active communication between students of different religions with tolerance as an attitude to maintain harmony in social relations during the study period and emphasize the need for integration of social aspects reflected in the study program curriculum so that the unique experience of each post-conflict student passed down from generation to generation can adapt to the campus environment commonly dubbed the "campus of basudara people".

Women's Communication Strategies in the Barbie Film

This study, conducted in a sociolinguistic setting, looks into the communication strategies utilized by female characters in the animated film "Barbie and the Magic of Pegasus." It looks at how these characters' verbal choices reflect and maybe perpetuate gendered norms and expectations, building on Coates' theory of conversational strategies. The study uses a qualitative analysis minimal responses, tag questions, questions, hedges, commands and directives, swearing and taboo language, as well as compliments used by the female characters in the film. This improves comprehension of the complicated connections between children's stories, language, gender, and social interaction. The goal is to provide a deeper understanding of the communicative preferences exhibited by these characters. Looking at women's words can reveal a lot about how gender identities are constructed and transmitted in animated storytelling. This study not only enriches the sociolinguistic academic discourse but also prompts a profound reflection on the role of language in shaping social norms. By providing a nuanced perspective on the communicative strategies of female characters, this research invites critical engagement with the dynamics of language, gender, and social interactions within the realm of animated narratives. This allows us to think more deeply about societal communication in movies. The results of this study indicate that women show characteristics of a gentler communication style with the use of limited gentle responses, subtle tag questions, and limited application of compliments. This preference prioritizes inclusion and brevity of communication over other techniques such as instructions, hedging, and taboo language. Keywords: Coates Theory, Communication Strategies, Female Characters

Dynamics of Male and Female Social Interactions in Students with Intellectual Disabilities during Puberty

Dynamics of Male and Female Social Interactions in Students with Intellectual Disabilities during Puberty

Social Masks and Identity Construction in Lualhati Bautista’s Bata... Pa'no Ka Ginawa?

This research employs a descriptive qualitative method, combining textual analysis with cultural and socio-cultural perspectives, to investigate the portrayal of social masks, identity construction, and resilience in Lualhati Bautista's novels, focusing on "Bata, Bata... Pa'no Ka Ginawa?" The study explores how selected characters navigate social roles, adopt personas, and engage in impression management within Filipino society. Through close reading and theoretical interpretation using Goffman's and Mead's frameworks, the research uncovers insights into the intricate dynamics of identity construction, social interaction, and resilience depicted in Bautista's narratives. Significant findings include resilience among characters and its intersection with identity construction and social interaction. Additionally, the study reveals the influence of cultural norms, historical events, and socio-economic factors on characters' identity construction and resilience strategies. It also highlights moments of authenticity, vulnerability, and resistance, analyzing how they challenge or reinforce social masks and identity performances. Overall, the research contributes to understanding the complexities of Filipino identity and resilience in contemporary society as portrayed in literature.

ОСОБЕННОСТИ ВЗАИМООТНОШЕНИЯ РОДИТЕЛЕЙ И УЧАЩИХСЯ СРЕДНЕЙ ШКОЛЫ В ИНКЛЮЗИВНОЙ СРЕДЕ

The study focuses on the dynamics of socialinteractions in an inclusive setting, the role of parents, and educational strategies aimed at optimizing the learning process and improving students’ social adaptation. Emphasis is placed on the practical aspects of pa-rentalinvolvementintheeducationalprocessandthedevelopment ofeffectiveapproachestostrengthenmutual understandingamong all participants in the educational environment.

Verbal behavior and the future of social science.

Natural language processing (NLP)-previously the domain of a select few language and computer scientists-is undergoing an unprecedented surge in popularity across disciplines. The ubiquity of language data, alongside extremely rapid methodological innovations, has magnetized the field, attracting researchers with the promise of measuring, forecasting, and understanding the most central questions in business, psychology, biology, sociology, the humanities, and beyond. The power of language analysis to reveal insights into human thought, feeling, and behavior has become a core interest emerging from recent technological advances, which are being probed to unearth deeply embedded truths about the human condition. However, NLP research has reached a critical juncture, sitting at the cusp of societal transformation in many aspects of daily life. The details of how NLP research develops over the next 3-5 years will define this transformation. In this emerging, near-infinite space of NLP-driven research, we provide a critical frame of reference for how, when, and why these technologies should evolve in a particularly transdisciplinary manner. Specifically, we discuss (a) the urgency of pairing existing and emerging NLP research with existing scientific knowledge, theory, and principles from the behavioral sciences; (b) the coevolution of NLP technologies; and (c) the practical implications and ethical consequences of expanding language analysis using broader psychosocial theories of the human condition. While our discussion focuses principally on using language as a window in the individual mind, this topic holds substantial implications for other disciplines and lines of inquiry, including the dynamics of social interaction and beyond. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The effects of game mechanics on user retention in using social live streaming services

PurposeSocial live streaming services (SLSS) have infused gamification into interface design and feature applications. Firms adopt gamification mechanisms to win customer loyalty in the live streaming and SLSS markets. Based on the mechanics-dynamics-aesthetics (MDA) framework and uses and gratifications 2.0 theory (UGT 2.0), this study aims to investigate the effects of game mechanics (mechanics) on enjoyment and user retention (aesthetics) through rewards and social interaction (dynamics) in the context of SLSS.Design/methodology/approachThis study used an online survey via Google Forms, SurveyCake and social media platforms like Facebook, Instagram and Line to collect data from 232 SLSS users in Taiwan. Partial least squares structural equation modeling (PLS-SEM) was adopted to analyze the data.FindingsThe results validated the relationships between game mechanics and dynamic elements (rewards and social interaction) that triggered aesthetic elements (enjoyment feelings) among users. In addition, users experienced a sense of enjoyment that led to usage retention when using the gamified SLSS. Further, this study found enjoyment crucial for users to stay interactive with gamified services.Originality/valueDriven by UGT 2.0, this study closed the gaps by integrating the MDA framework into the SLSS context and better understanding how game mechanics are connected to rewards and social interaction, leading to enjoyment and user retention when using SLSS. This study provides fresh insights into gamification-oriented SLSS practices. It offers significant theoretical and managerial implications and provides guidelines for SLSS platform operators on fostering user retention.

Do Social Interaction Mechanisms Affect University Reputation? Evidence from the UK Higher Education Sector

We investigate the influence of skilful utilization of social interaction dynamics on creating reputations for UK Higher Education Institutions (HEIs) during public funding cuts and scrutiny. The paper employs a content analysis method and follows an empirical design with a unique sample of 148 UK HEIs. To gauge reputation, we rely on participatory data from the Guardian newspaper's 2014–15 environmental and ethical performance ratings for the People &amp; Planet University League. Multiple regression analysis is applied to address the research hypotheses. The results indicate that open, accountable, and transparent sensemaking in sustainable development (SD) practices over the years is the predominant dynamic for enhancing HEIs’ reputation. This paper underscores the need to consider the institutional logics perspective as a theoretical foundation for a comprehensive understanding of the link between sustainability disclosure and an institution's reputation, image, and public goodwill within the higher education (HE) context. HEIs’ leadership should invest in SD and its associated disclosure practices. Policy‐makers and accounting regulators should establish consistent and comparable reporting requirements for sustainable performance within the HE sector. This paper is the first to empirically examine the direct impacts of HEIs’ compliance with sustainability duties on organizational performance.

The Dynamics of Social Interaction Among Evolved Model Agents.

We offer three advances to the perceptual crossing simulation studies, which are aimed at challenging methodological individualism in the analysis of social cognition. First, we evolve and systematically test agents in rigorous conditions, identifying a set of 26 "robust circuits" with consistently high and generalizing performance. Next, we transform the sensor from discrete to continuous, facilitating a bifurcation analysis of the dynamics that shows that nonequilibrium dynamics are key to the mutual maintenance of interaction. Finally, we examine agents' performance with partners whose neural controllers are different from their own and with decoy objects of fixed frequency and amplitude. Nonclonal performance varies and is not predicted by genotypic distance. Frequency-amplitude values that fool the focal agent do not include the agent's own values. Altogether, our findings accentuate the importance of dynamical and nonclonal analyses for simulated sociality, emphasize the role of dialogue between artificial and human studies, and highlight the contributions of simulation studies to understanding social interactions.

Dynamics of Information Flow and Task Allocation of Social Insect Colonies: Impacts of Spatial Interactions and Task Switching.

Models of social interaction dynamics have been powerful tools for understanding the efficiency of information spread and the robustness of task allocation in social insect colonies. How workers spatially distribute within the colony, or spatial heterogeneity degree (SHD), plays a vital role in contact dynamics, influencing information spread and task allocation. We used agent-based models to explore factors affecting spatial heterogeneity and information flow, including the number of task groups, variation in spatial arrangements, and levels of task switching, to study: (1) the impact of multiple task groups on SHD, contact dynamics, and information spread, and (2) the impact of task switching on SHD and contact dynamics. Both models show a strong linear relationship between the dynamics of SHD and contact dynamics, which exists for different initial conditions. The multiple-task-group model without task switching reveals the impacts of the number and spatial arrangements of task locations on information transmission. The task-switching model allows task-switching with a probability through contact between individuals. The model indicates that the task-switching mechanism enables a dynamical state of task-related spatial fidelity at the individual level. This spatial fidelity can assist the colony in redistributing their workforce, with consequent effects on the dynamics of spatial heterogeneity degree. The spatial fidelity of a task group is the proportion of workers who perform that task and have preferential walking styles toward their task location. Our analysis shows that the task switching rate between two tasks is an exponentially decreasing function of the spatial fidelity and contact rate. Higher spatial fidelity leads to more agents aggregating to task location, reducing contact between groups, thus making task switching more difficult. Our results provide important insights into the mechanisms that generate spatial heterogeneity and deepen our understanding of how spatial heterogeneity impacts task allocation, social interaction, and information spread.

Emotional Regulation Mechanisms of University Students in Group Work Situations.

A total of 107 students from a Chilean university and a Spanish university, all of them enrolled in the degree in Physical Activity and Sport Sciences, participated in the study. The instrument used was the Adaptative Instrument for Regulation of Emotions questionnaire. The analysis of the data shows that there are some significant differences (p ≤ 0.05), between the groups of students who worked virtually and those who worked in hybrid situations, in the aspects related to personal motivations (learn from my classmates, not to disappoint my working group, and enjoying the experience of working in a group). The students who worked online resolved conflicts mainly through individual regulation mechanisms with significant differences in relation to the students who worked in hybrid mode. No significant differences were found in the socioemotional challenges or in the balance of the metacognitive experience. The group that worked in hybrid learning valued group purposes over personal purposes and used the social regulation mechanism over individual regulation in conflict resolution. On the other hand, the group that worked virtually valued group and personal purposes equally and used the mechanism of individual regulation and social regulation to solve difficulties. Differences between students who worked in virtual and hybrid environments may be due to greater social interaction and group dynamics in hybrid environments, as well as differences in culture and access to resources and technology.

Enhancing ventrolateral prefrontal cortex activation mitigates social pain and modifies subsequent social attitudes: Insights from TMS and fMRI

Social pain, a multifaceted emotional response triggered by interpersonal rejection or criticism, profoundly impacts mental well-being and social interactions. While prior research has implicated the right ventrolateral prefrontal cortex (rVLPFC) in mitigating social pain, the precise neural mechanisms and downstream effects on subsequent social attitudes remain elusive. This study employed transcranial magnetic stimulation (TMS) integrated with fMRI recordings during a social pain task to elucidate these aspects. Eighty participants underwent either active TMS targeting the rVLPFC (n = 41) or control stimulation at the vertex (n = 39). Our results revealed that TMS-induced rVLPFC facilitation significantly reduced self-reported social pain, confirming the causal role of the rVLPFC in social pain relief. Functional connectivity analyses demonstrated enhanced interactions between the rVLPFC and the dorsolateral prefrontal cortex, emphasizing the collaborative engagement of prefrontal regions in emotion regulation. Significantly, we observed that negative social feedback led to negative social attitudes, whereas rVLPFC activation countered this detrimental effect, showcasing the potential of the rVLPFC as a protective buffer against adverse social interactions. Moreover, our study uncovered the impact role of the hippocampus in subsequent social attitudes, a relationship particularly pronounced during excitatory TMS over the rVLPFC. These findings offer promising avenues for improving mental health within the intricate dynamics of social interactions. By advancing our comprehension of the neural mechanisms underlying social pain relief, this research introduces novel intervention strategies for individuals grappling with social distress. Empowering individuals to modulate rVLPFC activation may facilitate reshaping social attitudes and successful reintegration into communal life.