Understanding Resident and Tourist Mobility in Venice Through Complex Networks

This study analyses the behaviour of Venice public transport network users, distinguishing between two profiles: residents and tourists. Using smart card data validations, four distinct complex networks are built based on user profiles during the regular and Carnival periods. The Louvain algorithm is utilised to detect communities within networks, identifying clusters of stops that travellers frequently visit together on the same day. Guimera's role detection algorithm categorises nodes into roles by employing two metrics that assess community membership and the degree of the community, thereby determining how specific nodes facilitate connections between different communities. The results reveal significant differences in mobility patterns between residents and tourists. Residents exhibit greater network resilience and stability across both periods, whereas tourists concentrate their trips during the Carnival period, leading to increased connectivity between specific nodes. These findings offer strategic insights for optimising public transportation networks based on user profiles.