Exploring Community Detection Algorithms and Their Applications in Social Networks

Community detection is a critical process for locating cohesive groups within social networks. The segment of strongly interconnected vertices into distinct communities yields valuable insights for various applications such as pattern recognition, recommendation systems, and data analysis. Since learners of higher education system are also on social networks forming strong communities, these can overlap with weaker natural communities. Identifying hidden weak communities within dominant ones is a challenge.This paper analyses Community detection algorithm for the online leaning student group recommendations based on interests. This study conducts a comparative analysis of existing community detection algorithms, assessing their performance across different parameters and applications, including online learning environments.