Analysis of social network metrics based on the model of random recursive tree

2020 ◽  
Vol 23 (1) ◽  
pp. 237-246
Author(s):  
Sanjay Kumar ◽  
Neeraj Bhat ◽  
B. S. Panda
Keyword(s):  
Social Network ◽  
Recursive Tree ◽  
Network Metrics

Social Networks and Social Complexity in Female-bonded Primates

2010 ◽  
Author(s):  
Julia Lehmann ◽  
Katherine Andrews ◽  
Robin Dunbar
Keyword(s):  
Social Network ◽  
Social Relationships ◽  
Social Complexity ◽  
Social Bonds ◽  
Primate Brain ◽  
The Social ◽  
Group Members ◽  
Primate Group ◽  
Network Metrics ◽  
The Relationship

Most primates are intensely social and spend a large amount of time servicing social relationships. The social brain hypothesis suggests that the evolution of the primate brain has been driven by the necessity of dealing with increased social complexity. This chapter uses social network analysis to analyse the relationship between primate group size, neocortex ratio and several social network metrics. Findings suggest that social complexity may derive from managing indirect social relationships, i.e. relationships in which a female is not directly involved, which may pose high cognitive demands on primates. The discussion notes that a large neocortex allows individuals to form intense social bonds with some group members while at the same time enabling them to manage and monitor less intense indirect relationships without frequent direct involvement with each individual of the social group.

scholarly journals Using Social Network Analysis and Social Capital to Identify User Roles on Polarized Political Conversations on Twitter

2019 ◽  
Vol 5 (2) ◽  
pp. 205630511984874 ◽  
Author(s):  
Raquel Recuero ◽  
Gabriela Zago ◽  
Felipe Soares
Keyword(s):  
Social Capital ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Opinion Leaders ◽  
Information Flows ◽  
Network Metrics ◽  
Network Analysis Metrics

In this article, we discuss the roles users play in political conversations on Twitter. Our case study is based on data collected in three dates during the former Brazilian president Lula’s corruption trial. We used a combination of social network analysis metrics and social capital to identify the users’ roles during polarized discussions that took place in each of the dates analyzed. Our research identified four roles, each associated with different aspects of social capital and social network metrics: activists, news clippers, opinion leaders, and information influencers. These roles are particularly useful to understand how users’ actions on political conversations may influence the structure of information flows.

Social network analysis of a gamified e-learning course: Small-world phenomenon and network metrics as predictors of academic performance

2016 ◽  
Vol 60 ◽  
pp. 312-321 ◽  
Author(s):  
Luis de-Marcos ◽  
Eva García-López ◽  
Antonio García-Cabot ◽  
José-Amelio Medina-Merodio ◽  
Adrián Domínguez ◽  
...  
Keyword(s):  
Academic Performance ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Small World ◽  
E Learning ◽  
Network Metrics ◽  
Predictors Of Academic Performance

Trust Modeling in a Virtual Organization Using Social Network Metrics

2011 ◽  
pp. 1179-1189
Author(s):  
Grzegorz Kolaczek
Keyword(s):  
Social Network ◽  
Virtual Communities ◽  
Sport Activity ◽  
Human Interaction ◽  
Mailing Lists ◽  
Trust Modeling ◽  
Trust Relation ◽  
Group Members ◽  
Fundamental Type ◽  
Network Metrics

One of the most important factors in human interaction and communication is trust. Each organization performing its quotidian tasks use intentionally or involuntary established trust relations to estimate the probability of achieving the expected results or the level of confidentiality. As in societies that evolved from real world relationship (e.g. school, office, sport activity, etc.) also in virtual communities (e.g. chat rooms, Web boards, mailing lists, etc.) trust is one of the most fundamental type of binding among the group members. In this article the trust relation establishment and evolution in virtual communities has been investigated. The presented model uses some typical parameters like node degree and centrality coefficient related to social network description and analysis.

Social Media Metrics in an Academic Setup

2017 ◽  
pp. 116-130
Author(s):  
Tasleem Arif ◽  
Rashid Ali
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Present Status ◽  
The Internet ◽  
Collaboration Networks ◽  
Different Types ◽  
Network Metrics ◽  
Network Analysis Metrics

Social media is perhaps responsible for largest share of traffic on the Internet. It is one of the largest online activities with people from all over the globe making its use for some sort of activity. The behaviour of these networks, important actors and groups and the way individual actors influence an idea or activity on these networks, etc. can be measured using social network analysis metrics. These metrics can be as simple as number of likes on Facebook or number of views on YouTube or as complex as clustering co-efficient which determines future collaborations on the basis of present status of the network. This chapter explores and discusses various social network metrics which can be used to analyse and explain important questions related to different types of networks. It also tries to explain the basic mathematics behind the working of these metrics. The use of these metrics for analysis of collaboration networks in an academic setup has been explored and results presented. A new metric called “Average Degree of Collaboration” has been defined to quantify collaborations within institutions.

Observing the Evolution of a Learning Community Using Social Network Analysis

2011 ◽  
pp. 215-231
Author(s):  
Francesca Grippa ◽  
Marco De Maggio ◽  
Angelo Corallo
Keyword(s):  
Social Network ◽  
Network Analysis ◽  
Community Development ◽  
Learning Communities ◽  
Learning Community ◽  
Learning Environments ◽  
Computer Scientists ◽  
Clear Identification ◽  
Network Metrics ◽  
Contribution Index

During the last decades, social and computer scientists have been focusing their efforts to study the effectiveness of collaboration in both working and learning environments. The main contributions clearly identify the importance of interactivity as the determinant of positive performances in learning communities where the supportive dimension of exchanges is balanced by the interactive one. In this chapter, authors describe a method based on social network metrics to recognize the stages of development of learning communities. The authors found that the evolution of social network metrics - such as density, betweenness centrality, contribution index, core/periphery structure – matched the formal stages of community development, with a clear identification of the forming, norming, and storming phases.

Sign in / Sign up

Export Citation Format

Share Document