The Social Network Analysis project focuses on the movie "Catch Me If You Can," a complex narrative with intricate character interactions. This analysis aims to unravel the underlying social structure using network analysis techniques, providing insights into the interconnectedness and relational dynamics of the characters.

The initial stages of the project involved constructing the network in Python, visualizing the graph, and calculating fundamental metrics like the number of nodes and edges, average degree, and density. These metrics offer an initial glimpse into the network's structure, indicating a moderate level of interconnectedness among nodes and a sparse graph, signifying that only a small fraction of possible connections are realized.

As the project progressed, we delved deeper, examining distances and diameters within the network. This approach aimed to understand the network's reachability and the efficiency of information flow among characters. The computation of average distance, average inverse distance and diameter provided valuable insights, revealing a rather tight network where individuals are closely knit in terms of social connections, a characteristic stemming from the central roles of Frank and Joe Shay, pivotal figures in the narrative. This tight-knit structure is evidenced by a low diameter and average shortest path length, underlining the network's small-world nature, characterized by efficient communication pathways and a closely connected social structure.