scholarly journals Simulating activation propagation in social networks using the graph theory

2010 ◽  
Vol 58 (3) ◽  
pp. 21-28 ◽  
Author(s):  
František Dařena ◽  
Alexander Troussov ◽  
Jan Žižka
Keyword(s):  
Social Networks ◽  
Graph Theory ◽  
Social Network ◽  
Network Formation ◽  
Directed Graphs ◽  
Good Method ◽  
Spreading Activation ◽  
The Social ◽  
Spreading Activation Algorithm ◽  
Social Network Formation

The social-network formation and analysis is nowadays one of objects that are in a focus of intensive research. The objective of the paper is to suggest the perspective of representing social networks as graphs, with the application of the graph theory to problems connected with studying the network-like structures and to study spreading activation algorithm for reasons of analyzing these structures. The paper presents the process of modeling multidimensional networks by means of directed graphs with several characteristics. The paper also demonstrates using Spreading Activation algorithm as a good method for analyzing multidimensional network with the main focus on recommender systems. The experiments showed that the choice of parameters of the algorithm is crucial, that some kind of constraint should be included and that the algorithm is able to provide a stable environment for simulations with networks.

scholarly journals Understanding the Social Networks That Form within the Context of an Obesity Prevention Intervention

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Sabina B. Gesell ◽  
Kimberly D. Bess ◽  
Shari L. Barkin
Keyword(s):  
Social Networks ◽  
Social Network ◽  
School Readiness ◽  
Obesity Prevention ◽  
Network Formation ◽  
Group Level ◽  
The Social ◽  
Similar Body ◽  
Child Bmi ◽  
Social Network Formation

Background. Antiobesity interventions have generally failed. Research now suggests that interventions must be informed by an understanding of the social environment.Objective. To examine if new social networks form between families participating in a group-level pediatric obesity prevention trial.Methods. Latino parent-preschool child dyads (N=79) completed the 3-month trial. The intervention met weekly in consistent groups to practice healthy lifestyles. The control met monthly in inconsistent groups to learn about school readiness. UCINET and SIENA were used to examine network dynamics.Results. Children’s mean age was 4.2 years (SD=0.9), and 44% were overweight/obese (BMI≥85th percentile). Parents were predominantly mothers (97%), with a mean age of 31.4 years (SD=5.4), and 81% were overweight/obese (BMI≥25). Over the study, a new social network evolved among participating families. Parents selectively formed friendship ties based on child BMI z-score, (t=2.08;P<.05). This reveals the tendency for mothers to form new friendships with mothers whose children have similar body types.Discussion. Participating in a group-level intervention resulted in new social network formation. New ties were greatest with mothers who had children of similar body types. This finding might contribute to the known inability of parents to recognize child overweight.

Enabling social networks in an R&D organization

2006 ◽  
Vol 25 (4) ◽  
pp. 237-246
Author(s):  
Tomas Hellström
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Qualitative Study ◽  
Network Formation ◽  
Higher Order ◽  
Practical Significance ◽  
Administrative Unit ◽  
High Level ◽  
Social Network Formation

This paper presents a qualitative study of mechanisms enabling social network formation in the R&D unit of a large technology-based organization. Drawing on interviews with 37 high-level technical and administrative unit members, a number of social network enablers could be discerned, which related to the need for effective location mechanisms, special “enrolment spaces”, and mechanisms for forging contacts. It was also possible to identify a number of higher-order factors for facilitation of network formation, namely hierarchical enablers and communicative and assimilative factors. Based on these results, the paper makes suggestions as to the theoretical and practical significance of social network enabling mechanisms in R&D organizations.

Feminist and Evolutionary Perspectives of Female-Female Competition, Status Seeking, and Social Network Formation

2015 ◽  
Author(s):  
Laurette T. Liesen
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Reproductive Success ◽  
Reproductive Strategies ◽  
Network Formation ◽  
Female Competition ◽  
Status Seeking ◽  
Social Network Formation ◽  
Evolutionary Perspectives

During the 1980s and 1990s, feminist evolutionists were instrumental in demonstrating that primate females, including girls and women, can be aggressive and seek status within their groups. Building on their insights, researchers from across disciplines have found that females use a variety of direct and indirect tactics as they pursue their reproductive success. To better understand women’s aggression and status seeking, one also must examine their social networks. Women must not only deal with the dynamics within their groups, they also must deal with pressures from other groups. Success in maintaining connections in one’s social network is vital for access to the various resources women need for their own reproductive success and to keep competitors in check. Overall, women’s social networks, while serving both supportive and competitive functions, profoundly impact on the reproductive future of women and especially the survival and future reproductive strategies of their children.

BEHAVIORAL FOUNDATIONS AND EQUILIBRIUM NOTIONS FOR SOCIAL NETWORK FORMATION PROCESSES

2004 ◽  
Vol 07 (01) ◽  
pp. 77-92 ◽  
Author(s):  
NICOLAS CARAYOL ◽  
PASCALE ROUX
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Formation Process ◽  
Network Formation ◽  
Small World ◽  
Payoff Function ◽  
Formation Processes ◽  
Limiting Distributions ◽  
Stochastically Stable ◽  
Social Network Formation

This paper develops a framework for studying social network formation. Partly built upon a formalism used in theoretical economics, the network formation process we introduce is locally driven by agents who maximize a given individual payoff function. We examine two simple models and observe the limiting distributions of stochastically stable networks. We find that these networks share some of the features observed for social networks. In particular, we find critical values of the parameters for which the selected networks exhibit small world properties.

A model of social network formation under the impact of structural balance

2016 ◽  
Vol 30 (09) ◽  
pp. 1650051 ◽  
Author(s):  
Pei Li ◽  
Jiajun Cheng ◽  
Yingwen Chen ◽  
Hui Wang
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Network Formation ◽  
Common Phenomenon ◽  
Structural Balance ◽  
Negative Links ◽  
Social Network Formation ◽  
The Impact ◽  
Negative Relationships ◽  
Industrial Societies

Social networks have attracted remarkable attention from both academic and industrial societies and it is of great importance to understand the formation of social networks. However, most existing research cannot be applied directly to investigate social networks, where relationships are heterogeneous and structural balance is a common phenomenon. In this paper, we take both positive and negative relationships into consideration and propose a model to characterize the process of social network formation under the impact of structural balance. In this model, a new node first establishes a link with an existing node and then tries to connect to each of the newly connected node’s neighbors. If a new link is established, the type of this link is determined by structural balance. Then we analyze the degree distribution of the generated network theoretically, and estimate the fractions of positive and negative links. All analysis results are verified by simulations. These results are of importance to understand the formation of social networks, and the model can be easily extended to consider more realistic situations.

Visualising Social Networks in Collaborative Environments

2010 ◽  
pp. 817-827
Author(s):  
Stephen T. O’Rourke ◽  
Rafael A. Calvo
Keyword(s):  
Social Networks ◽  
Graph Theory ◽  
Social Network ◽  
Social Networking ◽  
Collaborative Work ◽  
Mathematical Framework ◽  
Web Engineering ◽  
Simple Strategy ◽  
Collaboration Environment ◽  
The Social

Social networking and other Web 2.0 applications are becoming ever more popular, with a staggering growth in the number of users and the amount of data they produce. This trend brings new challenges to the Web engineering community, particularly with regard to how we can help users make sense of all this new data. The success of collaborative work and learning environments will increasingly depend on how well they support users in integrating the data that describes the social aspects of the task and its context. This chapter explores the concept of social networking in a collaboration environment, and presents a simple strategy for developers who wish to provide visualisation functionalities as part of their own application. As an explanatory case study, we describe the development of a social network visualisation (SNV) tool, using software components and data publicly available. The SNV tool is designed to support users of a collaborative application by facilitating the exploration of interactions from a network perspective. Since social networks can be large and complex, graph theory is commonly used as a mathematical framework. Our SNV tool integrates techniques from social networking and graph theory, including the filtering and clustering of data, in this case, from a large email dataset. These functions help to facilitate the analysis of the social network and reveal the embedded patterns of user behaviour in the underlying data.

scholarly journals Facilitating Intercultural Encounters with International Students: A Contribution to Inclusion and Social Network Formation

2021 ◽  
Vol 9 (3) ◽  
pp. 58-68 ◽  
Author(s):  
Katharina Resch ◽  
José Pedro Amorim
Keyword(s):  
Social Networks ◽  
Social Network ◽  
International Students ◽  
Social Inclusion ◽  
Network Formation ◽  
Adequate Funding ◽  
Intercultural Encounters ◽  
Inner Circle ◽  
Local Students ◽  
Social Network Formation

Higher education has become increasingly mobile and international, with many students taking the opportunity to study abroad during their studies. When they do so, forming and maintaining social networks is fundamental for their development of a sense of social inclusion. According to Coleman’s model of concentric circles, international students can establish networks with students from their own country (inner circle), with other international students (middle circle) and with local students (outer circle). This study explores various formats of organised student encounters in these three circles which contribute to the social inclusion of international students. The article is based on desk research of 15 formats of intercultural student encounters which facilitate social network formation during a study placement abroad in six countries in Europe. The findings show that all the studied formats of organised student encounters facilitate social networks in the middle and outer circles, while those in the inner circle are established by the students themselves and through informal social interaction. Formats embedded in the curriculum are most suited to facilitating social network formation throughout the academic year. Extracurricular formats, in contrast, tend to be single occasion activities without follow‐up. The study shows that universities can facilitate social network formation and assist social inclusion for international students through organised encounters in which international and local students meet. Organising such encounters does, however, require resources, evaluation, and adequate funding.

scholarly journals A METHOD TO IMPROVE THE TIME OF COMPUTING BETWEENNESS CENTRALITY IN SOCIAL NETWORK GRAPH

2019 ◽  
Vol 57 (3) ◽  
pp. 344
Author(s):  
Dung Xuan Nguyen ◽  
Ban Van Doan ◽  
Ngoc Thi Bich Do
Keyword(s):  
Social Networks ◽  
Graph Theory ◽  
Social Network ◽  
Execution Time ◽  
Betweenness Centrality ◽  
Computing Time ◽  
Network Graph ◽  
The Social

The Betweenness centrality is an important metric in the graph theory and can be applied in the analyzing social network. The main researches about Betweenness centrality often focus on reducing the complexity. Nowadays, the number of users in the social networks is huge. Thus, improving the computing time of Betweenness centrality to apply in the social network is neccessary. In this paper, we propose the algorithm of computing Betweenness centrality by reduce the similar nodes in the graph in order to reducing computing time. Our experiments with graph networks result shows that the computing time of the proposed algorithm is less than Brandes algorithm. The proposed algorithm is compared with the Brandes algorithm [3] in term of execution time.

scholarly journals Athlete Social Support Network Modeling Based on Modern Valence Bond Theory

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Ningshe Zhao
Keyword(s):  
Social Network ◽  
Network Formation ◽  
Valence Bond ◽  
Support Network ◽  
Network Nodes ◽  
Valence Bond Theory ◽  
Social Basis ◽  
The Social ◽  
Bond Theory ◽  
Social Network Formation

Based on the Valence Bond theory, an attempt is proposed to the complex network. The principle of chemical bonding of the basic particles that make up the substance creates a metaphor between the formation of social networks. By analyzing the integration of atoms by relying on the chemical bonds between particles, then the social basis for the connection between social network nodes should depend on the tangible or intangible attribute resources that characterize social capital around the main node. Based on the above analysis, the social node is divided into active nodes and passive nodes, and a dynamic model of social network formation is proposed, the Valence Bond model of social network. Through this model, the actual athlete group nodes are depicted, and the representation of the model and the evolution of network structure are given with the actual data.

scholarly journals Measurement of network-based and random meetings in social networks

2019 ◽  
pp. 765-779
Author(s):  
Pranav NERURKAR ◽  
MADHAV CHANDANE ◽  
SUNIL BHIRUD
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Relationship ◽  
Network Formation ◽  
Continuous Growth ◽  
The Social ◽  
Simulation Based ◽  
Suitable Structure ◽  
Block Models ◽  
Genesis Model

Social networks are created by the underlying behavior of the actors involved in them. Each actor has interactions with other actors in the network and these interactions decide whether a social relationship should develop between them. Such interactions may occur due to meeting processes such as chance-based meetings or network-based (choice) meetings. Depending upon which of these two types of interactions plays a greater role in creation of links, a social network shall evolve accordingly. This evolution shall result in the social network obtaining a suitable structure and certain unique features. The aim of this work is to determine the relative ratio of the meeting processes that exist between different actors in a social network and their importance in understanding the procedure of network formation. This is achieved by selecting a suitable network genesis model. For this purpose, different models for network genesis are discussed in detail and their differences are highlighted through experimental results. Network genesis models are compared and contrasted with other approaches available in the literature, such as simulation-based models and block models. Performance measures to compare the results of the network genesis models with baselines are statistics of networks recreated using the models. The socially generated networks studied here belong to various domains like e- commerce, electoral processes, social networking websites, peer to peer file-sharing websites, and Internet graphs. The insights obtained after analyzing these datasets by network genesis models are used for prescribing measures that could ensure continuous growth of these social networks and improve the benefits for the actors involved in them.

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