Statistical physics has proven to be a fruitful framework to describe phenomena outside the realm of traditional physics. Recent years have witnessed an attempt by physicists to study collective phenomena emerging from the interactions of individuals as elementary units in social structures. A wide list of topics are reviewed ranging from opinion and cultural and language dynamics to crowd behavior, hierarchy formation, human dynamics, and social spreading. The connections between these problems and other, more traditional, topics of statistical physics are highlighted. Comparison of model results with empirical data from social systems are also emphasized.

Statistical physics of social dynamics

https://science.sciencemag.org/content/sci/5/110/206.full.pdf

The american psychological association.

Many ``real-world'' networks are clearly defined while most ``social'' networks are to some extent subjective. Indeed, the accuracy of empirically-determined social networks is a question of some concern because individuals may have distinct perceptions of what constitutes a social link. One unambiguous type of connection is sexual contact. Here we analyze data on the sexual behavior of a random sample of individuals, and find that the cumulative distributions of the number of sexual partners during the twelve months prior to the survey decays as a power law with similar exponents $\alpha \approx 2.4$ for females and males. The scale-free nature of the web of human sexual contacts suggests that strategic interventions aimed at preventing the spread of sexually-transmitted diseases may be the most efficient approach.

The Web of Human Sexual Contacts

State-Trait Anxiety Inventoryによるペインクリニック外来患者の不安の評価

The Internet of Things vision: Key features, applications and open issues

The modeling of small group dynamics represents a hard challenge despite the effort of disciplines such as sociophysics and social psychology. The interaction between the complex topology of human social structures/communities and the cognitive processes characterizing humans at the microscopic level, are the focus of the classical social cognition paradigm, and it has been deeply researched in the last century. In the present study we used a web based Chat room as an experimental environment for the study of social interactions within a small group of people. The target of the present study is to explore the relations between the affinity among individual and their communication dynamics. We designed three different experimental tasks (social problem), with a crescent degree of social complexity, in order to test the impact of different social constraints on the evolution of the affinity network, as well as on the dynamics of communication. Our aim is to define the "cognitive recipes" used by the subjects to solve the required social problems. Our results show that the complexity of the social problem affects the relation between affinity and communication networks, influencing at the same time both affinity and opinion. We use the sociophysics and social cognitive models in order to interpret the results, showing the limits of the most diffused sociophysics models when aiming at forecasting the dynamics of a small group.

Human virtual communities: affinity and communication dynamics

We present a research framework consisting of a standard chat environment and a set of analytical tools, able to detect some relevant characteristics of the group dynamics of interacting people. The analysis is independent of the semantic content of the exchanged messages, and the standardized interface avoids hard-to-detect non-verbal communications, still providing the expression of emotional contents. This study proposes a quantitative approach to the investigation of the cognitive small group dynamics, considering the personal representation of the others, and communication dynamics. We developed a framework for the analysis that merges the complex network theory with concepts from social psychology and sociophysics. The focus of the framework is a quantitative investigation of how people explore and build their cognitive representation of the social space. Moreover two different experimental tasks have been proposed in order to investigate the role of some ecological constraints on the cognitive heuristics used by the subjects. The results show how people behave differently with respect to the task they are facing. In particular the absolute and the relative frequencies of the messages and their qualitative aspects significantly differ between the two conditions, as so as the cognitive strategies used by subjects to assess the affinity with the others. Keywords-Virtual Dynamics; Small Group; Social Psychology; Complex Systems

Virtual Small Group Dynamics:a Quantitative Experimental Framework

Online activities are a fundamental part of daily life in this digital era and Internet self-efficacy (ISE) became a central construct for the psychologists of virtual environments. The Internet Self-Efficacy Scale developed by Kim and Glassman (2013) is a recent, valid, and reliable 17-item test to assess the ISE. The aim of this research, composed by two studies, was to translate and validate the Italian version of the ISS. In study 1, we evaluated the factorial validity and internal consistency of the Italian version of the ISS on 3724 individuals. In study 2, we tested the ISS external validity relying on the Bergen Social Media Addiction Scale (BSMAS) and the Internet Addiction Scale (IAS) based on the answers of 244 participants. The findings supported the reliability and validity of the translated ISS and its use for assessing ISE on the Italian population. Implications for researchers and interventions are also discussed.

/pdf/italian-version-of-the-internet-self-efficacy-scale-internal-162kqf3k.pdf

Italian Version of the Internet Self-Efficacy Scale: Internal and External Validation

Current technological advancements have allowed robots to be successfully employed in the healthcare sector. However, the recently acquired ability of social robots to process social information and act according to it has potentially made them very well suited to support or conduct psychological interventions. The present paper carried out a systematic review of the available literature regarding social-robot-based interventions in psychological domains using preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. The inclusion criteria were: (i) publication date until 2020; (ii) being an empirical study, master thesis, or project report; (iii) written in English or Italian languages (the two languages spoken by the authors); (iv) published in a scholarly peer-reviewed journal or conference proceedings, or were Ph.D. or master’s theses; and (v) assessed “social robot”-based intervention in psychological domains. Overall, the review showed that three main areas may benefit from social-robot-based interventions: social skills, mood, and wellbeing (e.g., stress and anxiety levels). Interestingly, social robots seemed to have a performance comparable to, and sometimes even better than, human operators. The main, but not exclusive, target of robot-based interventions in the psychological field was children with autism spectrum disorder (ASD). As evidence is, however, still limited and in an embryonic state, deeper investigations are needed to assess the full potential of social robots for the purposes of psychological intervention. This is relevant, considering the role that social robots could have in overcoming barriers to access psychological assessment and therapies.

Robotic Psychology: A PRISMA Systematic Review on Social-Robot-Based Interventions in Psychological Domains

Humans create teams to be more successful in a large variety of tasks. Groups are characterized by an emergent property called collective intelligence, which leads them to be smarter than single individuals. Previous studies proved that collective intelligence characterizes both real and online environments, focusing on adults’ performances. In this work, we explored which factors promote group success in an offline and online logical task with adolescents. Five hundred and fifty high school students participated in the experiment and faced Raven’s Advanced Progressive Matrices, first by themselves using the computer, then in a group. Groups interactions could have been computer-mediated or face-to-face, and the participants were randomly assigned to one of the two experimental conditions. Results suggest that groups perform better than singles, regardless of the experimental condition. Among adolescents, online groups performance was negatively affected by participants’ average perception of group cohesion, the difficulty of the problem, and the number of communicative exchanges that occur in the interaction. On the contrary, the factors that improve their performances were the average intelligence of the teammates, their levels of neuroticism, and the group heterogeneity in terms of social abilities. This work contributes to the literature with a comprehensive model of collective intelligence among young people.

Andrea Guazzini

Papers

Human virtual communities: affinity and communication dynamics

Virtual Small Group Dynamics:a Quantitative Experimental Framework

Italian Version of the Internet Self-Efficacy Scale: Internal and External Validation

Robotic Psychology: A PRISMA Systematic Review on Social-Robot-Based Interventions in Psychological Domains

Adolescent’s Collective Intelligence: Empirical Evidence in Real and Online Classmates Groups