Graph Theory and Network Algorithms for Social Network Analysis

Abstract

Abstract: In order to analyse social networks, graph theory and network algorithms are essential tools. Understanding the intricate architecture and dynamics of social networks has become crucial due to the proliferation of online platforms and the expansion of data availability. The interdisciplinary nature of social network analysis is reflected in the reviewed literature, which includes contributions from computer science, mathematics, physics, and social sciences. It emphasises the significance of taking into account social networks' structural and behavioural features as well as its temporal dynamics and ever-evolving nature.It is clear from reading the cited publications that scholars have made considerable advancements in their understanding of social network analysis. To meet the obstacles offered by massive, real-world social networks, they have put forth creative algorithms, created fresh procedures, and introduced workable solutions. These studies also highlight the value of network research across a range of fields, including communication networks, organisational networks, and online social platforms.The results of this literature evaluation provide practitioners and researchers in the field of social network analysis with useful information. They give insights into cutting-edge procedures and algorithms, assisting in the choice and use of the most effective methods for analysing and deciphering social network data. The publications that have been examined add to the body of knowledge in graph theory and network algorithms for social network analysis, laying the groundwork for future developments in this quickly developing area.