Social Interaction Model Research Articles

Microblog Sentiment Orientation Detection Using User Interactive Relationship

The development and popularity of microblog have made sentiment analysis of tweets and Weibo an important research field. However, the characteristics of microblog message pose challenge for the sentiment analysis and mining. The existing approaches mostly focus on the message content and context information. In this paper, we propose a novel microblog sentiment analysis framework by incorporating the social interactive relationship factor in the content-based approach. By exploring the interactive relationship on social network based on posted messages, we build social interactive model to represent the opposition or acceptation behavior. Based on the interactive relationship model, the sentiment of microblog message with sparse emotion terms can be deduced and identified, and the sentiment uncertainty can be alleviated to some extent. Afterwards, we transform the classification problem into an optimization problem. Experimental results on Weibo data set indicate that the proposed method can outperform the baseline methods.

Stability of a spatial model of social interactions

We study a spatial model of social interactions. Though the properties of the spatial equilibrium have been largely discussed in the existing literature, the stability of equilibrium remains an unaddressed issue. Our aim is to fill up this gap by introducing dynamics in the model and by determining the stability of equilibrium. First we derive a variational equation useful for the stability analysis. This allows to study the corresponding eigenvalue problem. While odd modes are shown to be always stable, there is a single even mode of which stability depends on the model parameters. Finally various numerical simulations illustrate our theoretical results.

EarGram Actors: An Interactive Audiovisual System Based on Social Behavior

In multi-agent systems, local interactions among system components following relatively simple rules often result in complex overall systemic behavior. Complex behavioral and morphological patterns have been used to generate and organize audiovisual systems with artistic purposes. In this work, we propose to use the Actor model of social interactions to drive a concatenative synthesis engine called earGram in real time. The Actor model was originally developed to explore the emergence of complex visual patterns. On the other hand, earGram was originally developed to facilitate the creative exploration of concatenative sound synthesis. The integrated audiovisual system allows a human performer to interact with the system dynamics while receiving visual and auditory feedback. The interaction happens indirectly by disturbing the rules governing the social relationships amongst the actors, which results in a wide range of dynamic spatiotemporal patterns. A performer thus improvises within the behavioural scope of the system while evaluating the apparent connections between parameter values and actual complexity of the system output.

Fragmentasi Manusia dalam Kultur Makan Masa Kini

<p>Food has been one of the most important foundations of human history. Food functions as a statement of the self, a classification system, a way of social interaction, and even a cultural identity that it can be interpreted holistically. Food has been one of the most important elements that shape life and the history of human civilization. It demonstrates a kind of culture that signifies the dynamic of humanity from one era to the other. The expansion of food industry has brought a great impact on the revolution of social interaction model. However, a reduction of the food value is happening nowadays throughout the food culture, seeing it as simply as nutrition and economical commodity. Hedonism triggers the view of food as a tool to conquer the human desire, which actually never ceased even after being satisfied. A sort of ‘McDonaldization’ system is considered as a grand system of living that might have significantly changed many aspects of human life in this globalisation era. The <em>Branded Life</em> propaganda of the food industry seems to mislead people to continue their luxurious life. The fragmentation of human’s views on food becomes one of its consequences and in turn changes human’s respect of food within its holistic picture. The discussion now covers the social and spiritual dimensions. Today, the fragmented views of food have turned into a threat to humanity, but also a great opportunity, notwithstanding uncomfortable, to highlight the missing aspects of food in the midst of contemporary culture.</p>

"Targeting or supporting, what drives patterns of aggressive intervention in fights?".

GrooFiWorld is an individual-based, computational model of social interactions that can be used to examine factors underlying reciprocation and interchange of social behavior in primate societies. Individuals within GrooFiWorld are programed to maintain spatial proximity and thereby form a group. When an individual encounters another individual in its proximity, the individual attacks the other if the risk of losing is low. Otherwise, the individual considers grooming the other. Patterns of social behavior that emerge in the model resemble empirical data from primates. Triadic aggression emerges when an individual attacks one of the former combatants by chance immediately after an aggressive interaction, and reciprocation and interchange of grooming and support emerge even though individuals have no intention to help others or pay back services. The model generates predictions for patterns of contra-intervention that are counterintuitive within a framework of interchange of social services, such as that individuals receive more contra-intervention from those whom they groom more frequently. Here we tested these predictions in data collected on social interactions in a group of bonnet macaques (Macaca radiata). We confirmed the predictions of the model in the sense that contra-intervention was strongly correlated with dyadic aggression which suggests that contra-intervention is a subset of dyadic aggression. Adult females directed more contra-intervention to those individuals from whom they received more grooming. Further, contra-intervention was directed down the dominance hierarchy such that adult females received more contra-intervention from higher ranking females. Because these findings are consistent with the predictions from the GrooFiWorld model, they suggest that the distribution of interventions in fights is regulated by factors such as dominance rank and spatial structure rather than a motivation to help others and interchange social services.

Peer effects in sexual initiation: Separating demand and supply mechanisms

Most work on social interactions studies a single, composite effect of interactions within a group. Yet in the case of sexual initiation, there are two distinct social mechanisms—peer‐group norms and partner availability—with separate effects and different potential interventions. Here I develop an equilibrium search and matching model for first sexual partners that specifies distinct roles for these two mechanisms as part of demand and supply. I estimate the model using a national sample of high school students, with data over time on individual virginity status. The results indicate that peer‐group norms have a large effect on the timing of sexual initiation for both boys and girls. Changes in opposite‐gender search behavior (i.e., partner availability) also have a large impact on initiation rates for boys, but not for girls. Social interaction models mechanisms sexual activity youth structural estimation C31 C33 J13

Interpersonal Process of Emotional Labor: The Role of Negative and Positive Customer Treatment

Emotional labor refers to the process of regulating both feelings and expressions in response to the display rules for promoting organizational goals. Existing literature has provided strong evidence for the impact of emotional labor (i.e., surface acting and deep acting) on service employees’ emotional exhaustion. However, the empirical examination of the mechanisms underlying this association is largely missing from prior research. Drawing on the social interaction model of emotion regulation, this article reported 2 daily diary studies examining the role of customer treatment toward employees in channeling emotional labor's impact on employee emotional well‐being. Specifically, Study 1 measured emotional labor at the between‐person level as habitual emotional regulation strategies used by service employees, and Study 2 measured emotional labor at the within‐person level to capture its fluctuations. Results showed that employees engaging in more surface acting were more likely to receive negative treatment from customers, which in turn increased their negative affect and emotional exhaustion. Further, employees engaging in more deep acting were more likely to receive positive treatment from customers, which in turn increased their positive affect. Implications and limitations of these findings were discussed.

Two-Step Estimation of Incomplete Information Social Interaction Models with Missing Outcome Data

In this study, we consider linear social interaction models under incomplete information that allow for missing outcome data due to sample selection. For model estimation, assuming that each individual forms his/her belief about the other members' outcomes based on heterogeneous rational expectations, we propose a two-step series nonlinear least squares estimator. Both consistency and asymptotic normality of the estimator are established. As an empirical illustration, we apply the proposed model and method to National Longitudinal Study of Adolescent Health (Add Health) data in order to examine the impacts of friendship interactions on adolescents' academic achievements. We provide empirical evidence that the interaction effects are important determinants of grade point average, and that controlling for sample selection bias has certain impacts on the estimation results, particularly on the endogenous interaction effects.

Point-process models of social network interactions: Parameter estimation and missing data recovery

Electronic communications, as well as other categories of interactions within social networks, exhibit bursts of activity localised in time. We adopt a self-exciting Hawkes process model for this behaviour. First we investigate parameter estimation of such processes and find that, in the parameter regime we encounter, the choice of triggering function is not as important as getting the correct parameters once a choice is made. Then we present a relaxed maximum likelihood method for filling in missing data in records of communications in social networks. Our optimisation algorithm adapts a recent curvilinear search method to handle inequality constraints and a non-vanishing derivative. Finally we demonstrate the method using a data set composed of email records from a social network based at the United States Military Academy. The method performs differently on this data and data from simulations, but the performance degrades only slightly as more information is removed. The ability to fill in large blocks of missing social network data has implications for security, surveillance, and privacy.

Studying Social Interactions in Groupware Systems

Groupware Systems (GS) support groups of users to, via cooperation, coordination, and communication, achieve a common goal. Technological advance has caused the users requirements become more demanding for the GS, being required for the GS to include social interactions for improving the collaboration of users in a better way. Thereby, it is necessary to find techniques for enhancing and performing tasks in collaborative work. In this paper, we present a review about the works related to the interaction models. In addition, we present the results of an experimental study with 30 users aimed to evaluate the social interactions of a GS (a collaborative videogame - First Person Shooter). The results obtained show that the social interactions can still be improved in such systems, whereby we propose a conceptual model of social interactions to support the collaboration of users. In order to validate our approach we propose a prototype based on Multi-Agent Systems.

Adaptive Responses to Demographic Fragility: Mitigating Stochastic Effects in Early Island Colonization

This paper advances the debate regarding the social relations of prehistoric islanders beyond the dichotomy of isolation vs connectivity by proposing a general and cross-cultural model of adaptive behavioral responses to stochastically-forced demographic fragility. I show that smaller populations—more likely earlier in the settlement histories of islands—are more exposed to localized extinction via stochastic processes. To alleviate this greater degree of exposure, maintaining social links that allow for genetic flow between otherwise isolated populations should increase overall fitness. Conversely, as discrete populations expand, the imperative for access to a widely distributed metapopulation, and hence the need to maintain these links, should decrease. This is illustrated via simple network analysis. Potential venues for testing this general model are outlined; wider implications for the archaeology of colonization, and for spatial modeling of social interaction, are briefly discussed.

A Novel Statistical Model to Estimate Host Genetic Effects Affecting Disease Transmission.

There is increasing recognition that genetic diversity can affect the spread of diseases, potentially affecting plant and livestock disease control as well as the emergence of human disease outbreaks. Nevertheless, even though computational tools can guide the control of infectious diseases, few epidemiological models can simultaneously accommodate the inherent individual heterogeneity in multiple infectious disease traits influencing disease transmission, such as the frequently modeled propensity to become infected and infectivity, which describes the host ability to transmit the infection to susceptible individuals. Furthermore, current quantitative genetic models fail to fully capture the heritable variation in host infectivity, mainly because they cannot accommodate the nonlinear infection dynamics underlying epidemiological data. We present in this article a novel statistical model and an inference method to estimate genetic parameters associated with both host susceptibility and infectivity. Our methodology combines quantitative genetic models of social interactions with stochastic processes to model the random, nonlinear, and dynamic nature of infections and uses adaptive Bayesian computational techniques to estimate the model parameters. Results using simulated epidemic data show that our model can accurately estimate heritabilities and genetic risks not only of susceptibility but also of infectivity, therefore exploring a trait whose heritable variation is currently ignored in disease genetics and can greatly influence the spread of infectious diseases. Our proposed methodology offers potential impacts in areas such as livestock disease control through selective breeding and also in predicting and controlling the emergence of disease outbreaks in human populations.

Device-to-Device Link Admission Policy Based on Social Interaction Information

We propose an admission policy for device-to-device (D2D) communication link based on a social interaction model. We utilize prior information on user interactive statistics such as contact frequency and contact duration among potential D2D pairs to determine the success rate of message delivery. Targeting a particular delivery success rate, we further propose methods to identify admissible D2D links according to their statistical channel state information. The social-interaction-based D2D admission policy provides a real-life guideline for practical D2D underlay operation in cellular networks.

Minor Transnationalism in the Prehistoric Aegean? The Case of Phoenicians on Crete in the Early Iron Age

The study of population movements and cultural interaction, both large- and small-scale, has been increasingly important for understanding past societies and the archaeological remains of their material culture. As the result of long-term social and ideological practices in life and death, consumption and deposition patterns in the archaeological record are essential for viewing changes in cultural identities brought about by contact with other groups. In the Early Iron Age, groups of people we call “Phoenicians” set forth to various regions around the Mediterranean Sea and established predominantly colonial connections with local populations. While Phoenician presence is attested on the island of Crete, the available evidence does not reflect common trends in the archaeological remains of Phoenician colonial activity. Consequently, many debates exist on how to classify the interactions of Phoenicians and Cretans in the Early Iron Age. A reexamination of archaeological data associated with the Phoenician presence on Crete, however, provides an opportunity to test new theoretical models of transnational social interaction. In this article I suggest that the modern concept of minor transnationalism may be a useful tool to view this case of ancient cultural contact. In particular, I examine two examples of sanctuaries and cemeteries on Crete where Phoenician interactions with local populations have produced evidence for transnational spaces, which are created by the interconnections between agents of two liminal groups. By applying a modern theory to ancient evidence, this article will help expand the historical scope of transnationalism beyond strictly modern perspectives. In short, the application of transnationalism to the ancient past will provide a more transhistorical perspective on cultural contact.

The role of mitigation and strengthening cognitive operations in brand names design: a case study of Spanish and American wine brands

ABSTRACTDespite the relevance of powerful brands in the present-day market, research on the process of brand name design from a cognitive perspective focuses almost exclusively on the effects of the use of conceptual metaphor, and to a lesser extent, metonymy, overlooking the role played by other cognitive strategies. This paper analyzes the potentiality of mitigation and strengthening cognitive operations as tools for the systematic, risk-free design of new brand names with highly predictable and felicitous connotations. In particular, it focuses on their role in the systematic generation of axiologically positive brands in both Spanish and American wine labels, thus largely reducing the need for the costly and time-consuming cultural checks that branding companies need to run on new brand names before their commercial launching. In so doing, the interaction of the two aforementioned cognitive operations with a number of pragmatic principles and cultural models of social interaction, and their subservience to other cognitive operations, like those of comparison, correlation, and domain expansion and reduction, are also considered. The results of the study offer new insights on the semantics of commercial brand names which should prove useful for branding professionals, as well as data of interest to linguists dealing with inter-linguistic issues and cognitive modeling alike.

Speaking and Listening with the Eyes: Gaze Signaling during Dyadic Interactions.

Cognitive scientists have long been interested in the role that eye gaze plays in social interactions. Previous research suggests that gaze acts as a signaling mechanism and can be used to control turn-taking behaviour. However, early research on this topic employed methods of analysis that aggregated gaze information across an entire trial (or trials), which masks any temporal dynamics that may exist in social interactions. More recently, attempts have been made to understand the temporal characteristics of social gaze but little research has been conducted in a natural setting with two interacting participants. The present study combines a temporally sensitive analysis technique with modern eye tracking technology to 1) validate the overall results from earlier aggregated analyses and 2) provide insight into the specific moment-to-moment temporal characteristics of turn-taking behaviour in a natural setting. Dyads played two social guessing games (20 Questions and Heads Up) while their eyes were tracked. Our general results are in line with past aggregated data, and using cross-correlational analysis on the specific gaze and speech signals of both participants we found that 1) speakers end their turn with direct gaze at the listener and 2) the listener in turn begins to speak with averted gaze. Convergent with theoretical models of social interaction, our data suggest that eye gaze can be used to signal both the end and the beginning of a speaking turn during a social interaction. The present study offers insight into the temporal dynamics of live dyadic interactions and also provides a new method of analysis for eye gaze data when temporal relationships are of interest.

ENRICHING VOCABULARY THROUGH SOCIAL INTERACTION MODEL

The objective of this research was to find out the significance of the students’ achievement before and after learning vocabulary through Social Interaction Method at the eight class of SMP Guppi Samata Gowa. This research employed pre-experimental method with one group pretest and posttest design. There were two variables, namely dependent variable was the students’ vocabulary achievement and the independent variable was the application of Social Interaction Model in teaching vocabulary. The population was the students in the eighth grade of SMP Guppi Samata Gowa. The sample of the research consisted of 50 students which were taken by using cluster total sampling, 25 students were taken as an experimental class and 25 students were taken as a controlled class. The instrument was vocabulary test in the multiple-choice test. The multiple choice test consists of 10 items that consist of five choices. The findings of the research were students vocabulary used pre-test and post-test. The result of the data indicated that there was a significant difference between students’ post-test in experimental class and controlled class. The mean score of posttest (61.6) in experimental class was greater than the mean score of posttest (56) in controlled class and the standard deviation of posttest (8.94) in experimental class was greater than the standard deviation of posttest in controlled class (6.29). From t-test, the researcher found that the value of t-test (2.553) was greater than t-table (2.021) at the level of significance 0.05 with the degree of freedom (df) = 48.

MGlu5-GABAB interplay in animal models of positive, negative and cognitive symptoms of schizophrenia

Diverse preclinical studies exploiting the modulation of the GABAergic and/or glutamatergic system in brain via metabotropic receptors suggest their potential therapeutic utility. GS39783 and CDPPB, positive allosteric modulators of GABAB and mGlu5 receptors, were previously shown to reverse behavioral phenotypes in animal models to mimic selected (predominantly positive) symptoms of schizophrenia. In the present study we investigated the activity of selected GABAB (GS39783 and CGP7930) and mGlu5 (CDPPB) positive allosteric modulators. We focused mainly on the aspects of their efficacy in the models of negative and cognitive symptoms of schizophrenia. We used modified swim test, social interactions (models of negative symptoms) and novel object recognition (model of cognitive disturbances). The activity of the compounds was also tested in haloperidol-induced catalepsy test. The mutual interaction between GABAB/mGlu5 ligands was investigated as well. In the second part of the study, DHPG-induced PI hydrolysis in the presence of GABAB receptor antagonist (SKF97541), and SKF97541-induced inhibition of cAMP formation in the presence of DHPG, was performed. Both mGlu5 and GABAB receptor modulators effectively reversed MK-801-induced deficits in behavioral models of schizophrenia. Moreover, the concomitant administration of sub-effective doses of CDPPB and GS39783 induced a clear antipsychotic-like effect in all the procedures used, except DOI-induced head twitches. The concomitant administration of group I mGlu and GABAB agonists did not displayed any synergistic effects in vitro. Summing up, an activation of both types of receptor may be a promising mechanism for the development of novel antipsychotic drugs, efficacious toward positive, negative and cognitive symptoms.

Social interactions and college enrollment: A combined school fixed effects/instrumental variables approach

This paper provides some of the first evidence of peer effects in college enrollment decisions. There are several empirical challenges in assessing the influences of peers in this context, including the endogeneity of high school, shared group-level unobservables, and identifying policy-relevant parameters of social interactions models. This paper addresses these issues by using an instrumental variables/fixed effects approach that compares students in the same school but different grade-levels who are thus exposed to different sets of classmates. In particular, plausibly exogenous variation in peers’ parents’ college expectations are used as an instrument for peers’ college choices. Preferred specifications indicate that increasing a student’s exposure to college-going peers by ten percentage points is predicted to raise the student’s probability of enrolling in college by 4 percentage points. This effect is roughly half the magnitude of growing up in a household with married parents (vs. an unmarried household).

Gender Segregation in Occupations: The Role of Tipping and Social Interactions

This paper documents that the dynamics of occupational segregation are highly nonlinear and exhibit tipping patterns. Occupations experience discontinuous declines in net male employment growth at tipping points ranging from 25% to 45% (from 13% to 30%) female in white-collar (blue-collar) occupations from 1940 to 1990. These patterns appear consistent with a Schelling (1971) social interaction model where tipping results from male preferences toward the fraction female in their occupation. Supporting the model’s predictions, evidence from the General Social Survey indicates that tipping points are lower in regions where males hold more sexist attitudes toward the appropriate role of women.