Graph Theory: A Comprehensive Survey about Graph Theory Applications in Computer Science and Social Networks

TLDR

Graph theory provides versatile tools for computer science tasks such as web document clustering, cryptography, algorithm analysis, electronic circuit simplification, and for modeling and analyzing social network structures, operations, and user behavior. This survey aims to comprehensively review graph theory applications in social networks while also briefly outlining its uses in computer science through practical examples. The authors present a concise overview of graph theory’s applications in computer science and social networks, illustrating each with concrete examples.

Abstract

Graph theory (GT) concepts are potentially applicable in the field of computer science (CS) for many purposes. The unique applications of GT in the CS field such as clustering of web documents, cryptography, and analyzing an algorithm’s execution, among others, are promising applications. Furthermore, GT concepts can be employed to electronic circuit simplifications and analysis. Recently, graphs have been extensively used in social networks (SNs) for many purposes related to modelling and analysis of the SN structures, SN operation modelling, SN user analysis, and many other related aspects. Considering the widespread applications of GT in SNs, this article comprehensively summarizes GT use in the SNs. The goal of this survey paper is twofold. First, we briefly discuss the potential applications of GT in the CS field along with practical examples. Second, we explain the GT uses in the SNs with sufficient concepts and examples to demonstrate the significance of graphs in SN modeling and analysis.