Social Interaction Model Research Articles

Analyzing the effects of memory biases and mood disorders on social performance

Realistic models of decision-making and social interactions, considering the nature of memory and biases, continue to be an area of immense interest. Emotion and mood are a couple of key factors that play a major role in decisions, nature of social interactions, size of the social network, and the level of engagement. Most of the prior work in this direction focused on a single trait, behavior, or bias. However, this work builds an integrated model that considers multiple traits such as loneliness, the drive to interact, the memory, and mood biases in an agent. The agent system comprises of rational, manic, depressed, and bipolar agents. The system is modeled with an interconnected network, and the size of the personal network of each agent is based on its nature. We consider a game of iterated interactions where an agent cooperates based on its past experiences with the other agent. Through simulation, the effects of various biases and comparative performances of agent types is analyzed. Taking the performance of rational agents as the baseline, manic agents do much better, and depressed agents do much worse. The payoffs also exhibit an almost-linear relationship with the extent of mania. It is also observed that agents with stronger memory perform better than those with weaker memory. For rational agents, there is no significant difference between agents with a positive bias and those with a negative bias. Positive bias is linked with higher payoffs in manic and bipolar agents. In depressed agents, negative bias is linked with higher payoffs. In manic agents, an intermediate value of mood dependence offers the highest payoff. But the opposite is seen in depressed agents. In bipolar agents, agents with weak mood dependence perform the best.

Heterogeneity in SIR epidemics modeling: superspreaders and herd immunity

Deterministic epidemic models, such as the Susceptible-Infected-Recovered (SIR) model, are immensely useful even if they lack the nuance and complexity of social contacts at the heart of network science modeling. Here we present a simple modification of the SIR equations to include the heterogeneity of social connection networks. A typical power-law model of social interactions from network science reproduces the observation that individuals with a high number of contacts, “hubs” or “superspreaders”, can become the primary conduits for transmission. Conversely, once the tail of the distribution is saturated, herd immunity sets in at a smaller overall recovered fraction than in the analogous SIR model. The new dynamical equations suggest that cutting off the tail of the social connection distribution, i.e., stopping superspreaders, is an efficient non-pharmaceutical intervention to slow the spread of a pandemic, such as the Coronavirus Disease 2019 (COVID-19).

Equilibrium Computation in Discrete Network Games

Counterfactual policy evaluation often requires computation of game-theoretic equilibria. We provide new algorithms for computing pure-strategy Nash equilibria of games on networks with finite action spaces. The algorithms exploit the fact that many agents may be endowed with types such that a particular action is a dominant strategy. These agents can be used to partition the network into smaller subgames whose equilibrium sets may be more feasible to compute. We provide bounds on the complexity of our algorithms for models obeying certain restrictions on the strength of strategic interactions. These restrictions are analogous to the assumption in the widely used linear-in-means model of social interactions that the magnitude of the endogenous peer effect is bounded below one. For these models, our algorithms have complexity O_p(n^c), where the randomness is with respect to the data-generating process, n is the number of agents, and c depends on the strength of strategic interactions. We also provide algorithms for computing pairwise stable and directed Nash stable networks in network formation games.

Migration-induced transition in social structures: a view through the Sakoda model of social interactions

We study the dynamics of three populations evolving in a two-dimensional discrete grid according to rules of attraction, rejection, or indifference following the framework of the seminal model by Sakoda and we apply it to migration phenomena. An interesting feature of the Sakoda model is the existence of a Potts-like energy which, as a common principle, decreases as time passes by. Here we consider the evolution of two populations until stabilization, then, we perturb this attractor by the inclusion of a third arrival: the immigrants. We show the conditions under which this irruption does not alter significantly the previous attractor (a sociological morphostatic behaviour) or it is dramatically changed (morphogenetic behaviour). We observe empirically that for a morphostatic behaviour the energy decreases while for morphogenesis this energy increases, revealing an escalation of social tension.

Pharmacology profile of F17464, a dopamine D3 receptor preferential antagonist

F17464 (N-(3-{4-[4-(8-Oxo-8H-[1,3]-dioxolo-[4,5-g]-chromen-7-yl)-butyl]-piperazin-1-yl}-phenyl)-methanesulfonamide, hydrochloride) is a new potential antipsychotic with a unique profile. The compound exhibits high affinity for the human dopamine receptor subtype 3 (hD3) (Ki = 0.17 nM) and the serotonin receptor subtype 1a (5-HT1a) (Ki = 0.16 nM) and a >50 fold lower affinity for the human dopamine receptor subtype 2 short and long form (hD2s/l) (Ki = 8.9 and 12.1 nM, respectively). [14C]F17464 dynamic studies show a slower dissociation rate from hD3 receptor (t1/2 = 110 min) than from hD2s receptor (t1/2 = 1.4 min) and functional studies demonstrate that F17464 is a D3 receptor antagonist, 5-HT1a receptor partial agonist. In human dopaminergic neurons F17464 blocks ketamine induced morphological changes, an effect D3 receptor mediated. In vivo F17464 target engagement of both D2 and 5-HT1a receptors is demonstrated in displacement studies in the mouse brain. F17464 increases dopamine release in the rat prefrontal cortex and mouse lateral forebrain - dorsal striatum and seems to reduce the effect of MK801 on % c-fos mRNA medium expressing neurons in cortical and subcortical regions. F17464 also rescues valproate induced impairment in a rat social interaction model of autism. All the neurochemistry and behavioural effects of F17464 are observed in the dose range 0.32–2.5 mg/kg i.p. in both rats and mice. The in vitro - in vivo pharmacology profile of F17464 in preclinical models is discussed in support of a therapeutic use of the compound in schizophrenia and autism.

Social Interaction and Information Diffusion in Social Internet of Things: Dynamics, Cloud-Edge, Traceability

Social Internet of Things (SIoT), integrating the social networks and Internet of Things (IoT), leads to heterogeneous interactions of thing to thing, human to human, and human to thing, which in turn generates exploded information. Hence, as the soul of SIoT, information with its interaction and diffusion, records the track of humans and things and contains the hidden value for social administration and people's lives. Therefore, how to characterize the interplay between behavior spreading and information diffusion in SIoT is essential to predict and manage the information. Motivated by this, a more comprehensive understanding of the coupled modeling of social interaction and information diffusion processes in SIoT is conceived first. With the widespread adoption of cloud-edge computing, different nodes have different consciousness on information. Hence, a cloud-edge-aided information diffusion model is proposed for efficient interactions, which incorporates the role of edge in timely processing and feedback. On this basis, a blockchain-based cloud-edge SIoT architecture is proposed for traceability and security of information diffusion. Furthermore, the dynamical analysis of the coupled model in SIoT is provided, which illustrates the outbreak threshold, stability, and scale of information propagation. An interesting finding is that interactive behavior spreading only influences the final size of information propagation, not the spreading threshold. Extensive simulation results and detailed performance analysis verify the theoretical results, which are beneficial to provide traceable dissemination so as to find the most influential node and control the scale of information diffusion.

La sociedad y la comunicación desde la perspectiva de Manuel Castells de sociedad red

La sociedad red es una manera de entender el mundo propuesta por Manuel Castells desde hace ya más de dos décadas. A partir de dicho concepto el autor español explica cómo es que el advenimiento de las tecnologías digitales generó cambios tan profundos que impactaron no solo en los procesos de producción, sino en la manera en la que las personas viven su cotidianidad. Es decir, de acuerdo con Castells, en este nuevo contexto (2009, p. 154) los individuos están reconstruyendo el modelo de interacción social con la ayuda de las nuevas posibilidades tecnológicas para crear un nuevo modelo de sociedad: la sociedad red. Así, los conceptos sociedad y comunicación cobran un nuevo sentido en dicho paradigma. Por ello, el presente artículo analizará tales acepciones subrayando la manera en la que Castells las concibe y las relaciona a su vez con otros conceptos (como la libertad y la tecnología). De igual manera, tales conceptos (sociedad y comunicación) serán contrastados con la visión que aportan Byung-Chul Han (con el cual se contrastará el concepto de sociedad) y Marshall McLuhan (con quien se contrastará el concepto comunicación).
 De tal manera que el análisis aquí propuesto buscará contribuir a entender las amplias implicaciones contenidas en el concepto sociedad red no solo a partir de la visión de Manuel Castells, sino además buscando la comparación y el contraste con otras visiones que de los mismos conceptos poseen otros autores, en este caso Han y McLuhan.

AXIOLOGICAL DETERMINANTS OF REFRAMING IN LAUGHTER CULTURE

The article is devoted to the analysis of the conceptual field of designation of axiological determinants of reframing in a laughing culture, exploring the specifics of the functional load of laughter and its manipulative potential in contemporary society. Addressing to the characteristics of the psychotechnology of semantic reformatting in a laughing culture, the axiological factors of interpretive interactions in various discursive contexts and semantic invariations are examined (examples of political laughter, actual quarantine jokes and viral memes).Conceptual inversions, which in tangible culture have tangible value dynamics, are studied in the aspect of their manipulative and actualization capabilities. It is proved that the laughable effect in reframing techniques is achieved due to an unexpected and sudden change in the stereotypical course of events based on the logic of recurrence and breakdown of expected patterns, based primarily on a change in the value perception of a particular event or phenomenon, as well as its contextual rethinking and creation of cognitive metaphors. Accordingly, the use of metaphors is defined as a special means of reframing, which actualizes the necessary cognitive parameters due to unexpected conceptual games with binary oppositions, semantic subtext, and open metaphorical profiling, which has a powerful effect of latent influence in modeling of social interaction. An analysis of the mutual influence of traditional laughing theories (contradiction, criticism and liberation) allows us to highlight such common signs of laughter as ambivalence, paradox, sociality, solidarity, conventionality, creativity, dialogism, dynamism, reflexivity. An important aspect of the axiology of laughter is defined as a focused attitude to values and anti-values, which can be a means of displaying alternative points of view on the world, giving rise to new contexts of “comic” understanding of reality in game configurations of socially-situational roles and characteristics of conceptual characters of laughter culture.

When a Leader has to Put on an Act: A Test of Dual-Process Model of Leaders' Emotional Labor

Drawing on Gardner et al.’s (2009) model of leader’s emotional labor and authenticity and Côté’s (2005) social interaction model of emotion regulation and work strain, we explore how leader’s surface and deep acting is associated with leader’s felt authenticity, which is further related to leader’s emotional exhaustion (intrapersonal process). We also explore how leader’s surface and deep acting is associated with follower’s perceived leader authenticity, which is further related to follower’s affective trust in leader (interpersonal process). Moreover, we investigate whether follower’s affective trust in leader affects leader’s emotional exhaustion. Using survey research, we obtained 166 pairs of leader-follower dyad data in organizations at Taiwan. The results showed that, regarding intrapersonal process, leader’s surface (deep) acting is negatively (positively) related to felt authenticity, which serves as a mediator and is further related to emotional exhaustion. Regarding interpersonal process, leader’s surface acting is negatively related to follower’s perceived leader authenticity, which serves as a mediator and further related to trust in leader. In addition, follower’s trust in leader is associated with leader’s emotional exhaustion. Our study contributes to existing literature by demonstrating that leader’s deep acting may be a compromise between emotional labor and authenticity, and that Gardner et al.’s (2009) model can be integrated with Côté’s (2005) model.

Network Competition and Team Chemistry in the NBA

–We consider a heterogeneous social interaction model where agents interact with peers within their own network but also interact with agents across other (non-peer) networks. To address potential endogeneity in the networks, we assume that each network has a central planner who makes strategic network decisions based on observable and unobservable characteristics of the peers in her charge. The model forms a simultaneous equation system that can be estimated by quasi-maximum likelihood. We apply a restricted version of our model to data on National Basketball Association games, where agents are players, networks are individual teams organized by coaches, and competition is head-to-head. That is, at any time a player only interacts with two networks: their team and the opposing team. We find significant positive within-team peer-effects and both negative and positive opposing-team competitor-effects in NBA games. The former are interpretable as “team chemistries” which enhance the individual performances of players on the same team. The latter are interpretable as “team rivalries,” which can either enhance or diminish the individual performance of opposing players.

Two tales of complex system analysis: MaxEnt and agent-based modeling

Over the recent four decades, agent-based modeling and maximum entropy modeling have provided some of the most notable contributions applying concepts from complexity science to a broad range of problems in economics. In this paper, we argue that these two seemingly unrelated approaches can actually complement each other, providing a powerful conceptual/empirical tool for the analysis of complex economic problems. The maximum entropy approach is particularly well suited for an analytically rigorous study of the qualitative properties of systems in quasi-equilibrium. Agent-based modeling, unconstrained by either equilibrium or analytical tractability considerations, can provide a richer picture of the system under study by allowing for a wider choice of behavioral assumptions. In order to demonstrate the complementarity of these approaches, we use here two simple economic models based on maximum entropy principles – a quantal response social interaction model and a market feedback model –, for which we develop agent-based equivalent models. On the one hand, this allows us to highlight the potential of maximum entropy models for guiding the development of well-grounded, first-approximation agent-based models. On the other hand, we are also able to demonstrate the capabilities of agent-based models for tracking irreversible and out-of-equilibrium dynamics as well as for exploring the consequences of agent heterogeneity, thus fundamentally improving on the original maximum entropy model and potentially guiding its further extension.

Adjusted QMLE for the spatial autoregressive parameter

One simple, and often very effective, way to attenuate the impact of nuisance parameters on maximum likelihood estimation of a parameter of interest is to recenter the profile score for that parameter. We apply this general principle to the quasi-maximum likelihood estimator (QMLE) of the autoregressive parameter λ in a spatial autoregression. The resulting estimator for λ has better finite sample properties compared to the QMLE for λ, especially in the presence of a large number of covariates. It can also solve the incidental parameter problem that arises, for example, in social interaction models with network fixed effects. However, spatial autoregressions present specific challenges for this type of adjustment, because recentering the profile score may cause the adjusted estimate to be outside the usual parameter space for λ. Conditions for this to happen are given, and implications are discussed. For inference, we propose confidence intervals based on a Lugannani–Rice approximation to the distribution of the adjusted QMLE of λ. Based on our simulations, the coverage properties of these intervals are excellent even in models with a large number of covariates.

S218. TAURINE DOES NOT PREVENT SOCIAL DEFICITS INDUCED BY MK-801 IN ADULT ZEBRAFISH

BackgroundCognitive and negative symptoms are the core reason for the functional deficits experienced by patients with schizophrenia. Drugs that can modulate these symptoms are especially needed since no progress has been achieved in the last few decades with currently available antipsychotics. Taurine is an amino acid not used for protein synthesis but widely distributed in mammalian tissues. In the central nervous system, it has been shown to act as an inhibitory neuromodulator and possess neuroprotective, antioxidant and immunomodulatory properties. Decreased plasma and brain levels of taurine have been reported in patients as well as in animal models of schizophrenia. Furthermore, taurine improved symptoms and was well tolerated in a clinical trial of patients with first-episode psychosis. We investigated whether taurine counteracts social deficits in a zebrafish model of social interaction following acute exposure to MK-801 (dizocilpine), an NDMA antagonist commonly used in schizophrenia animal models.MethodsNinety-six 3-month-old wild-type zebrafish (Danio rerio, 50:50 male:female ratio) were used. For the social interaction test, animals were individually placed in a beaker with 200 mL of tank water (control) or taurine solution (42, 150 and 400 mg/L) for 20 minutes, and then exposed to water or MK-801 (5 µM) for another 20 minutes (n = 12 animals per group). Immediately after the treatments, zebrafish were transferred to the social interaction apparatus, a tank virtually divided in 3 vertical zones and sided by an empty tank and a tank containing 10 zebrafish. Behavior was recorded for 7 minutes and the last 5 were analyzed by automated tracking with the software ANY-Maze. The time spent in the stimulus zone was measured as a proxy for social interaction; total distance traveled was also computed. Data were analyzed by two-way ANOVA.ResultsMK-801 increased the total distance traveled (F1,88 = 4.935, p = 0.0289) and reduced the time spent in the tank zone next to the conspecifics (F1,88 = 23.14, p < 0.0001). No main effects of taurine or interaction effects were observed on locomotor or social interaction parameters.DiscussionAlthough taurine has been shown to increase social interaction in rats and modulate shoaling behavior in ethanol-exposed zebrafish, it had not been tested against social deficits induced by NMDA antagonists. We observed that taurine did not counteract the hyperlocomotion and social deficit induced by acute exposure to MK-801 in zebrafish. As schizophrenia etiology has been linked to cortical and hippocampal disruption in GABAergic signaling, taurine may be effective as a preventive treatment in early neurodevelopmental stages. Further testing using animal models that more closely resemble the course of schizophrenia are thus needed to investigate the potential of this molecule.

A Statistical Mechanics Approach to the Study of Energy Use Behaviour

This paper proposes a statistical mechanical model for the energy conservation behaviour of energy users. The model was inspired by the multipopulation Curie-Weiss model and the discrete choice with social interaction model. We demonstrate that the model integrates the sociopsychological, the economic, and the energy technologist viewpoints to energy management, allowing us to subject these perspectives to an empirical study.

Exploring the role of context on racially responsive supervision: The racial identity social interaction model.

Supervision may be an ideal format for training psychologists to be racially and culturally responsive because supervisors can tailor interventions to fit supervisees’ individual developmental needs. Nevertheless, over 30 years ago, counseling psychology researchers began identifying harmful effects of racially and culturally unresponsive supervision from the perspectives of supervisees. Missing from the literature has been empirical evidence from the perspectives of supervisors themselves. Moreover, research has failed to explore the influence of context (i.e., mental health sites) on supervision that addresses race and culture. The present study explored supervisors’ perspectives and experiences as they pertained to (a) providing racially and culturally responsive supervision, (b) the racial climate of their mental health work environments, and (c) influences of their institutional racial climates on their supervision practices as they pertained to race and culture. Interviews with psychologists, who identified as Black (n = 4) and White (n = 4), were analyzed using directed content analysis guided by the Racial Identity Social Interaction Model. Core domains and themes from the analysis drew connections between the supervisors’ perceptions of the racial climate of their institution and the challenges of supervising on race and culture. Findings from the study highlight the ways in which supervisors in mental health settings attempt to protect their supervisees in environments in which they often feel unprotected. Limitations and implications of the study for supervision theory, research, and practice are discussed.

Computing semiparametric efficiency bounds in discrete choice models with strategic-interactions and rational expectations

This paper computes semiparametric efficiency bounds for finite-dimensional parameters in discrete choice models with nonparametric regressors in the form of conditional expectations. These can include expectations about exogenous events as well as expectations about the choices of other agents. Thus, the models studied here include incomplete-information games, social-interactions models as well as single-agent discrete choice models with uncertainty as special cases. Our bounds rely on the assumption of rational expectations and on regularity conditions of equilibrium beliefs. The paper focuses on binary-choice models but the derivation of the bounds illustrates how our approach can be extended to multinomial choice cases. Explicit efficiency bound expressions for the models examined here had not been derived before. Furthermore, since we also characterize the efficient influence functions, our results can also potentially be used to construct semiparametrically efficient estimators for these models.

Linking Mechanisms between Attachment Quality During Infancy and Preschoolers’ Social Competence: Focusing on Continuity of Maternal Parenting Stress, Social Interaction, and Warmth

Objectives This study examined an integrated model of maternal parenting stress, social interaction, and warmth as linking mechanisms between preschooler’s attachment quality at age 1 and social competence at age 6. Methods Participants were 172 preschoolers (89 boys and 83 girls all aged 6) and their mothers recruited for the in-depth Korea Child Panel Study. Results Attachment security at age 1 indirectly affected preschoolers’ social competence at age 6, mediated by the continuity of maternal parenting stress from age 2 to 6 and the continuity of maternal social interaction and warmth from age 2 to 6. Additionally, maternal parenting stress affected maternal parenting behavior during the same period. Attachment security at age 1 did not directly affect preschoolers’ social competence at age 6. Conclusion This study showed that the parenting environment and maternal social interaction and warmth should be considered to explain the effects of attachment security during infancy on preschoolers’ social competence. Keywords: attachment security during infancy, preschoolers’ social competence, maternal parenting stress, maternal social interaction and warmth, continuity of caregiving

Exploring peer effects in education in Latin America and the Caribbean

This paper assesses peer group influence on academic performance of primary school students in Latin America and the Caribbean. Based on TERCE data set, we investigate peer effects in mathematics, language and sciences tests outcomes among sixth grade students. We apply a social interaction model which allows to identify endogenous and exogenous peer effects while controlling for group-level fixed effects. We explore some heterogeneities related to the school type (private, public or rural). The estimates suggest the existence of endogenous peer effects but their magnitude and significance depend on subject and school type.

Equilibrium computation in discrete network games

Counterfactual policy evaluation often requires computation of game‐theoretic equilibria. We provide new algorithms for computing pure‐strategy Nash equilibria of games on networks with finite action spaces. The algorithms exploit the fact that many agents may be endowed with types such that a particular action is a dominant strategy. These agents can be used to partition the network into smaller subgames whose equilibrium sets may be more feasible to compute. We provide bounds on the complexity of our algorithms for models obeying certain restrictions on the strength of strategic interactions. These restrictions are analogous to the assumption in the widely used linear‐in‐means model of social interactions that the magnitude of the endogenous peer effect is bounded below one. For these models, our algorithms have complexityOp(nc), where the randomness is with respect to the data‐generating process,nis the number of agents, andcdepends on the strength of strategic interactions. We also provide algorithms for computing pairwise stable and directed Nash stable networks in network formation games.

Dynamic Spatial Panel Models: Networks, Common Shocks, and Sequential Exogeneity

This paper considers a class of generalized methods of moments (GMM) estimators for general dynamic panel models, allowing for weakly exogenous covariates and cross‐sectional dependence due to spatial lags, unspecified common shocks, and time‐varying interactive effects. We significantly expand the scope of the existing literature by allowing for endogenous time‐varying spatial weight matrices without imposing explicit structural assumptions on how the weights are formed. An important area of application is in social interaction and network models where our specification can accommodate data dependent network formation. We consider an exemplary social interaction model and show how identification of the interaction parameters is achieved through a combination of linear and quadratic moment conditions. For the general setup we develop an orthogonal forward differencing transformation to aid in the estimation of factor components while maintaining orthogonality of moment conditions. This is an important ingredient to a tractable asymptotic distribution of our estimators. In general, the asymptotic distribution of our estimators is found to be mixed normal due to random norming. However, the asymptotic distribution of our test statistics is still chi‐square.