The use of social network analysis in different fields

Jiaqi Zhou

doi:10.54254/2755-2721/5/20230677

Research Article

Open access

Published on 31 May 2023

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Zhou,J. (2023). The use of social network analysis in different fields. Applied and Computational Engineering,5,697-703.

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The use of social network analysis in different fields

Jiaqi Zhou *^,1,

¹ School of computer science, Hertfordshire University, Hatfield, AL10 9AB, United Kingdom

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/5/20230677

Abstract

Social network analysis is a well-established research method in sociology. Some scholars also refer to this quantitative approach to graph theory as network science. As research intensified in the 1970s, it gained the attention of researchers in many other fields and has become an interdisciplinary research method. Social network analysis collects data from multiple sources and unearths new information by building network structures.The constructed network topology diagram and the calculated network properties are eventually analysed and generalised to produce further research results. The use of social network analysis (SNA) in a few different fields—tourism, society, transportation, citation, viral communication, medical education, and economic geography—is reviewed in this essay. Social network analysis is a quantitative analysis method that blends multiple disciplines. Various relationships are quantified through the construction of networks and property analysis. The paper is categorized according to the different fields of application. The different applications of social network analysis in various fields show its general and specific analytical approach.

Keywords

network science, social network analysis(SNA), complex networks.

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Cite this article

Zhou,J. (2023). The use of social network analysis in different fields. Applied and Computational Engineering,5,697-703.

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About volume

Volume title: Proceedings of the 3rd International Conference on Signal Processing and Machine Learning

Conference website: http://www.confspml.org

ISBN：978-1-915371-57-7(Print) / 978-1-915371-58-4(Online)

Conference date: 25 February 2023

Editor：Omer Burak Istanbullu

Series: Applied and Computational Engineering

Volume number: Vol.5

ISSN：2755-2721(Print) / 2755-273X(Online)

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