Centrality in Social Network Analysis: A Comprehensive Review for Students

Year : 2023 | Volume :01 | Issue : 02 | Page : 1-8
By

Rajesh Yadav,

  1. Assistant Professor, Department of Computer Science, SIES College Of Arts, Science & Commerce (Autonomous), Maharashtra, India

Abstract

Centrality, a fundamental concept in social network analysis (SNA), plays a pivotal role in understanding the structural dynamics and information flow within networks. This studyoffers an extensive examination of centrality metrics and their utilization in diverse fields. We begin by defining centrality and exploring its significance in characterizing the importance of nodes within a network. Subsequently, we delve into the literature review by different authors and most employed centrality metrics, including degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality, elucidating their underlying mathematical foundations and practical implications.Furthermore, the studydiscusses the strengths and limitations of each centrality measure, offering insights into their suitability for different network structures and research objectives. Additionally, we examine real-world applications of centrality in fields such as social sciences, epidemiology, organizational behavior, and information retrieval, highlighting the diverse contexts in which centrality analysis proves invaluable.This review serves as a comprehensive resource for researchers, practitioners, and enthusiasts in the field of social network analysis, offering a nuanced understanding of centrality measures and their broad-ranging applications across disciplines. Major focus is to make students in undergraduate degree and post-graduationaware about centrality measures in social network analysis.

Keywords: Degree centrality, betweenness centrality, SNA, centrality metrics

[This article belongs to International Journal of Data Structure Studies (ijdss)]

How to cite this article:
Rajesh Yadav. Centrality in Social Network Analysis: A Comprehensive Review for Students. International Journal of Data Structure Studies. 2023; 01(02):1-8.
How to cite this URL:
Rajesh Yadav. Centrality in Social Network Analysis: A Comprehensive Review for Students. International Journal of Data Structure Studies. 2023; 01(02):1-8. Available from: https://journals.stmjournals.com/ijdss/article=2023/view=126341

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Regular Issue Subscription Review Article
Volume 01
Issue 02
Received September 20, 2023
Accepted October 3, 2023
Published October 25, 2023

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