Speaker: Nathan Smith, Senior Data Scientist, Neo4j
Session type: Full Length
Abstract: Congratulations, your Graph Data Science Community Detection Algorithm has completed successfully! Now, how should you interpret the results and explain them to your colleagues? In this session, you'll learn how statistics such as modularity, conductance, and clustering coefficient can help you decide if your communities are cohesive enough to be meaningful. They can also help you choose the most meaningful result from the output of multiple differently configured Community Detection Algorithm runs. We will also look at ways to describe the communities that emerge from Community Detection Algorithms, which includes looking at the distributions of property values and finding the nodes that are most central within each community.