The Louvain Modularity algorithm is a community detection algorithm used to evaluate social structures in networks, including Twitter, LinkedIn, and YouTube. It measures the quality of an assignment of nodes to communities by comparing their relationship density to a suitably defined random network. The algorithm has been applied to various domains, such as recommending subreddits based on user behavior and extracting topics from online social platforms. However, it also has limitations, including a resolution limit that can make it difficult to detect small communities in large networks, and a degeneracy problem where there are multiple community assignments with similar modularity scores. The algorithm has been successfully applied to real-world data sets, including a graph of users and friends, which was used to demonstrate its capabilities. Next week's focus will be on the Triangle Count and Average Clustering Coefficient algorithm.