  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.
