Social network analysis (SNA) is the examination of social networks to comprehend participant behaviour and organisation. With heterogeneity and interdependencies posing as a major challenge, social network analysis (SNA) acts as a sustainable technique to study large-scale complicated social interactions. It offers quantitative techniques and topological metrics to analyse a network's topology in order to support transdisciplinary applications. This paper delves into the intricate digital landscapes of online social networks, aiming to elucidate the interconnectedness among social groups within these dynamic spaces. Through an exploratory investigation, we employ advanced network analysis techniques to map out the intricate web of connections that define the social fabric of digital platforms. By scrutinizing the structural characteristics of these networks, we uncover clusters and communities that delineate the underlying social groups and their interactions. Our findings shed light on the complex dynamics of online social behaviour, offering insights into the formation, evolution, and interplay of interconnected social groups in digital spaces. This study not only enhances our understanding of online social networks but also provides valuable implications for various fields, including sociology, computer science, and digital marketing. An important problem in social networking analysis is community detection.

Social network analysis (SNA) is the examination of social networks to comprehend participant behaviour and organisation.