Social Network Analysis Metrics and Their Application in Microbiological Network Studies

2014 ◽  
pp. 251-260 ◽  
Author(s):  
Juliana Saragiotto Silva ◽  
Nancy de Castro Stoppe ◽  
Tatiana Teixeira Torres ◽  
Laura Maria Mariscal Ottoboni ◽  
Antonio Mauro Saraiva
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Studies ◽  
Network Analysis Metrics

scholarly journals A Brief Overview of Social Network Analysis and its Current State within Romanian Sociology

2013 ◽  
Vol 3 (3) ◽  
pp. 5-11
Author(s):  
Marian-Gabriel Hâncean
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
International Relations ◽  
Early Spring ◽  
Research Topics ◽  
Political Sciences ◽  
Current State ◽  
Wide Range ◽  
Network Studies

Abstract The field of social network studies has been growing within the last 40 years, gathering scholars from a wide range of disciplines (biology, chemistry, geography, international relations, mathematics, political sciences, sociology etc.) and covering diverse substantive research topics. Using Google metrics, the scientific production within the field it is shown to follow an ascending trend since the late 60s. Within the Romanian sociology, social network analysis is still in his early spring, network studies being low in number and rather peripheral. This note gives a brief overview of social network analysis and makes some short references to the current state of the network studies within Romanian sociology

scholarly journals Social Network Analysis Visualization

2015 ◽  
pp. 257-270
Author(s):  
Mohana Shanmugam ◽  
Yusmadi Yah Jusoh ◽  
Rozi Nor Haizan Nor ◽  
Marzanah A. Jabar
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Online Social Network ◽  
Future Research ◽  
Research Gaps ◽  
The Social ◽  
Network Studies ◽  
Academic Study

The social network surge has become a mainstream subject of academic study in a myriad of disciplines. This chapter posits the social network literature by highlighting the terminologies of social networks and details the types of tools and methodologies used in prior studies. The list is supplemented by identifying the research gaps for future research of interest to both academics and practitioners. Additionally, the case of Facebook is used to study the elements of a social network analysis. This chapter also highlights past validated models with regards to social networks which are deemed significant for online social network studies. Furthermore, this chapter seeks to enlighten our knowledge on social network analysis and tap into the social network capabilities.

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 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.

scholarly journals Understanding Classrooms through Social Network Analysis: A Primer for Social Network Analysis in Education Research

2014 ◽  
Vol 13 (2) ◽  
pp. 167-178 ◽  
Author(s):  
Daniel Z. Grunspan ◽  
Benjamin L. Wiggins ◽  
Steven M. Goodreau
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Interactions ◽  
Human Subjects ◽  
Relational Data ◽  
Undergraduate Biology ◽  
Collection Data ◽  
Generative Processes ◽  
Network Studies

Social interactions between students are a major and underexplored part of undergraduate education. Understanding how learning relationships form in undergraduate classrooms, as well as the impacts these relationships have on learning outcomes, can inform educators in unique ways and improve educational reform. Social network analysis (SNA) provides the necessary tool kit for investigating questions involving relational data. We introduce basic concepts in SNA, along with methods for data collection, data processing, and data analysis, using a previously collected example study on an undergraduate biology classroom as a tutorial. We conduct descriptive analyses of the structure of the network of costudying relationships. We explore generative processes that create observed study networks between students and also test for an association between network position and success on exams. We also cover practical issues, such as the unique aspects of human subjects review for network studies. Our aims are to convince readers that using SNA in classroom environments allows rich and informative analyses to take place and to provide some initial tools for doing so, in the process inspiring future educational studies incorporating relational data.

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