scholarly journals Academic benefit of outgroup contact for immigrant and nonimmigrant students

2019 ◽  
Vol 22 (3) ◽  
pp. 419-433 ◽  
Author(s):  
Ralf Wölfer ◽  
Daniel H. Caro ◽  
Miles Hewstone
Keyword(s):  
Academic Achievement ◽  
Social Network ◽  
Cognitive Abilities ◽  
Multilevel Models ◽  
Immigrant Students ◽  
Social Network Data ◽  
The Social ◽  
Network Connectedness ◽  
Total Network ◽  
Country Specific

Based on social network theories, outgroup contact does not only improve intergroup relations, but can also facilitate the academic development of students due to the social capital and the uniquely supportive information and resources it provides. In the present study, 12,376 students (14.42 years; 50% girls; 38% immigrant students) from 591 classes across three countries (Germany, the Netherlands, and Sweden) provided information on social network data, academic achievement, socioeconomic status (SES), and cognitive ability. Social network analysis determined the intergroup network connectedness of students. As expected, country-specific multilevel models reveal a positive linear relationship between outgroup contact and academic achievement for immigrant students in all models, and a negative curvilinear (i.e., concave) relationship between outgroup contact and academic achievement for nonimmigrant students in 2 out of 3 models, while controlling for SES, cognitive abilities, and total network integration. These findings suggest the academic value of outgroup contact for immigrant students and signal its potential for nonimmigrant students.

The Multilevel p2 Model

Methodology ◽  
2006 ◽  
Vol 2 (1) ◽  
pp. 42-47 ◽  
Author(s):  
Bonne J. H. Zijlstra ◽  
Marijtje A. J. van Duijn ◽  
Tom A. B. Snijders
Keyword(s):  
Social Network ◽  
Network Data ◽  
Mcmc Algorithm ◽  
Independent Observation ◽  
Single Observation ◽  
Multiple Networks ◽  
Social Network Data ◽  
Multiple Observations ◽  
Practical Support ◽  
The Social

The p 2 model is a random effects model with covariates for the analysis of binary directed social network data coming from a single observation of a social network. Here, a multilevel variant of the p 2 model is proposed for the case of multiple observations of social networks, for example, in a sample of schools. The multilevel p 2 model defines an identical p 2 model for each independent observation of the social network, where parameters are allowed to vary across the multiple networks. The multilevel p 2 model is estimated with a Bayesian Markov Chain Monte Carlo (MCMC) algorithm that was implemented in free software for the statistical analysis of complete social network data, called StOCNET. The new model is illustrated with a study on the received practical support by Dutch high school pupils of different ethnic backgrounds.

scholarly journals Frequency of Recent Binge Drinking Is Associated With Sex-Specific Cognitive Deficits: Evidence for Condition-Dependent Trait Expression in Humans

2020 ◽  
Vol 18 (4) ◽  
pp. 147470492095444
Author(s):  
Liana S. E. Hone ◽  
John E. Scofield ◽  
Bruce D. Bartholow ◽  
David C. Geary
Keyword(s):  
Binge Drinking ◽  
Cognitive Abilities ◽  
Social Cognitive ◽  
Multilevel Models ◽  
Cognitive Task ◽  
A Priori ◽  
Visuospatial Abilities ◽  
The Social ◽  
Binge Drinkers ◽  
Visuospatial Tasks

Evolutionary theory suggests that commonly found sex differences are largest in healthy populations and smaller in populations that have been exposed to stressors. We tested this idea in the context of men’s typical advantage (vs. women) in visuospatial abilities (e.g., mental rotation) and women’s typical advantage (vs. men) in social-cognitive (e.g., facial-expression decoding) abilities, as related to frequent binge drinking. Four hundred nineteen undergraduates classified as frequent or infrequent binge drinkers were assessed in these domains. Trial-level multilevel models were used to test a priori Sex × Group (binge drinking) interactions for visuospatial and social-cognitive tasks. Among infrequent binge drinkers, men’s typical advantage in visuospatial abilities and women’s typical advantage in social-cognitive abilities was confirmed. Among frequent binge drinkers, men’s advantage was reduced for one visuospatial task (Δ d = 0.29) and eliminated for another (Δ d = 0.75), and women’s advantage on the social-cognitive task was eliminated (Δ d = 0.12). Males who frequently engaged in extreme binges had exaggerated deficits on one of the visuospatial tasks, as did their female counterparts on the social-cognitive task. The results suggest sex-specific vulnerabilities associated with recent, frequent binge drinking, and support an evolutionary approach to the study of these vulnerabilities.

scholarly journals Designing Educational Analytics Tools Using Visualization Based on Behavioral, Motivational, and Social Network Data

2019 ◽  
pp. 81-93
Author(s):  
Iliya L. Musabirov ◽  
Keyword(s):  
Social Network ◽  
Social Values ◽  
Network Data ◽  
Network Approach ◽  
Social Network Data ◽  
Use Of Data ◽  
University Courses ◽  
The Social ◽  
Social Network Approach ◽  
Visualization Tools

The article presents a description of the approach to the use of data visualization in various educational Analytics tools when building University courses. In addition to the analysis of educational behavior, socio-psychological approaches, including the theory of expectations and social values, and the social network approach, are separately considered as prospects for analysis. An example of designing training Analytics using modern data analysis and visualization tools is analyzed.

Social Network Analysis in Marketing

E-Marketing ◽  
2012 ◽  
pp. 185-197
Author(s):  
Przemyslaw Kazienko ◽  
Piotr Doskocz ◽  
Tomasz Kajdanowicz
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Relationships ◽  
Network Data ◽  
Social Network Data ◽  
The Social ◽  
Targeted Marketing ◽  
Potential Customers ◽  
Demographic Features

The chapter describes a method how to perform a classification task without any demographic features and based only on the social network data. The concept of such collective classification facilitates to identify potential customers by means of services used or products purchased by the current customers, i.e. classes they belong to as well as using social relationships between the known and potential customers. As a result, a personalized offer can be prepared for the new clients. This innovative marketing method can boost targeted marketing campaigns.

Social Network Analysis in Marketing

2011 ◽  
pp. 271-283
Author(s):  
Przemyslaw Kazienko ◽  
Piotr Doskocz ◽  
Tomasz Kajdanowicz
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Relationships ◽  
Network Data ◽  
Social Network Data ◽  
The Social ◽  
Targeted Marketing ◽  
Potential Customers ◽  
Demographic Features

The chapter describes a method how to perform a classification task without any demographic features and based only on the social network data. The concept of such collective classification facilitates to identify potential customers by means of services used or products purchased by the current customers, i.e. classes they belong to as well as using social relationships between the known and potential customers. As a result, a personalized offer can be prepared for the new clients. This innovative marketing method can boost targeted marketing campaigns.

Social Networks and Crime: Pitfalls and Promises for Advancing the Field

2019 ◽  
Vol 2 (1) ◽  
pp. 99-122 ◽  
Author(s):  
Katherine Faust ◽  
George E. Tita
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Potential Measurement ◽  
Fully Integrated ◽  
Social Network Data ◽  
The Past ◽  
Dynamic Social Network ◽  
Criminological Research ◽  
The Social ◽  
Criminological Theories

Over the past decade, a considerable literature has emerged within criminology stemming from the collection of social network data and the adoption of social network analysis by a cadre of scholars. We review recent contributions to four areas of crime research: co-offending networks, illicit networks, gang-rivalry networks, and neighborhoods and crime. Our review highlights potential pitfalls that one might encounter when using social networks in criminological research and points to fruitful directions for further research. In particular, we recommend paying special attention to the clear specifications of what ties in the network are assumed to be doing, potential measurement weaknesses that can arise when using police or investigative data to construct a network, and understanding dynamic social network processes related to criminological outcomes. We envision a bright future in which the social network perspective will be more fully integrated into criminological theories, analyses, and applications.

Genetic Algorithm Applied in the Social Network Data Analysis

2013 ◽  
Vol 427-429 ◽  
pp. 2188-2191
Author(s):  
Lei Liu ◽  
Quan Bao Gao
Keyword(s):  
Genetic Algorithm ◽  
Social Networks ◽  
Social Network ◽  
Data Analysis ◽  
Rapid Development ◽  
Virtual Community ◽  
Social Network Data ◽  
Starting Point ◽  
The Social ◽  
Optimal Data Analysis

The rapid development of network and information technology makes the network become the indispensable part in people's life. Network design uses email as a starting point, instead of actual letters. Then Happy Nets, BBS etc. are evolved from it, with virtual as their major feature. In the process of social networks evolution, the personal image transformed from the actual into the virtual one. All this has contributed to the birth of the social network, which then makes the contacts among people presenting the feature of network expansion and cost reduction. The popular social network nowadays is considered to be social plus network, namely, through the network, as a carrier, people are connected to form a virtual community with certain characteristics. Based on the genetic algorithm and genetic coding technology, the article is designed to make the optimal data analysis and create a optimistic cyber environment in the process of the social networks explosive development.

Exploring the Moderating Effects of Cognitive Abilities on Social Competence Intervention Outcomes

2017 ◽  
Vol 42 (1) ◽  
pp. 84-107 ◽  
Author(s):  
Janine P. Stichter ◽  
Melissa J. Herzog ◽  
Stephen P. Kilgus ◽  
Alexander M. Schoemann
Keyword(s):  
Social Competence ◽  
Cognitive Abilities ◽  
Rating Scales ◽  
Multilevel Models ◽  
Teacher Behavior ◽  
Significant Degree ◽  
Multiple Time ◽  
Post Intervention ◽  
The Social ◽  
Social Competence Deficits

Many populations served by special education, including those identified with autism, emotional impairments, or students identified as not ready to learn, experience social competence deficits. The Social Competence Intervention-Adolescents’ (SCI-A) methods, content, and materials were designed to be maximally pertinent and applicable to the social competence needs of early adolescents (i.e., age 11-14 years) identified as having scholastic potential but experiencing significant social competence deficits. Given the importance of establishing intervention efficacy, the current paper highlights the results from a four-year cluster randomized trial (CRT) to examine the efficacy of SCI-A (n = 146 students) relative to Business As Usual (n = 123 students) school-based programming. Educational personnel delivered all programming including both intervention and BAU conditions. Student functioning was assessed across multiple time points, including pre-, mid-, and post-intervention. Outcomes of interest included social competence behaviors, which were assessed via both systematic direct observation and teacher behavior rating scales. Data were analyzed using multilevel models, with students nested within schools. Results suggested after controlling for baseline behavior and student IQ, BAU and SCI students differed to a statistically significant degree across multiple indicators of social performance. Further consideration of standardized mean difference effect sizes revealed these between-group differences to be representative of medium effects (d > .50). Such outcomes pertained to student (a) awareness of social cues and information, and (b) capacity to appropriately interact with teachers and peers. The need for additional power and the investigation of potential moderators and mediators of social competence effectiveness are explored.

Application of Computer System in the Study of Sociology

2014 ◽  
Vol 926-930 ◽  
pp. 1680-1683
Author(s):  
Ying Ming Xu ◽  
Shu Juan Jin
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Computer Algorithms ◽  
Useful Knowledge ◽  
Social Network Data ◽  
Analysis Task ◽  
Original Analysis ◽  
The Social ◽  
The Relationship

With the development of information technology, more and more data about social to be collected. If we can analyze them effectively, it will help people to understand sociological understanding, promoting the development of social science. But the increasing amount of data and analysis to put forward a huge challenge. Now the social networks have already surpassed the processing ability of the original analysis means, must use a more effective tool to complete the analysis task. The computer as a way of helping people from massive data to find the potential useful knowledge tools, play an important role in many fields. Social network analysis, also known as link mining, refers to the handling of the relationship between social network data in the computer method. In this paper, the methods of computer and the social network analysis was introduced in this paper and the computer algorithms are summarized in the application of social network analysis.

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