This study applies social network analysis (SNA) to map and analyze literary networks in St Petersburg from 1999 to 2019, using data from the 'SPbLitGuide' newsletter. By examining co-participation in literary events, we reveal the dynamics and structures of these networks, identifying key communities and influential figures. Our network graph, consisting of 14,066 nodes and 127,068 edges, represents a highly interconnected and cohesive small-world network with robust local clustering and extensive collaboration. Focusing on core participants, we refined the graph and applied community detection methods to identify distinct groups with specific aesthetic preferences and personal connections. These findings provide insights into the structure and dynamics of literary groups in St. Petersburg and provide a foundation for further research in the digital humanities.