References: Community and Similarity

1. Community Structure - Wikipedia - Overview of community detection in networks including modularity optimization, hierarchical clustering, and label propagation methods. Directly applicable to discovering informal team structures.

2. Louvain Method - Wikipedia - Explains the Louvain algorithm for modularity-based community detection, the most widely used method for identifying clusters in large organizational networks with near-linear time complexity.

3. Jaccard Index - Wikipedia - Mathematical definition and applications of the Jaccard similarity coefficient for comparing set membership. Used to measure overlap between employees' collaboration networks, skill sets, and project portfolios.

4. Structural Holes: The Social Structure of Competition - Ronald Burt - Harvard University Press (1992) - Foundational work on how bridging positions between communities create competitive advantage. Burt's framework informs how community boundaries and boundary-spanning roles are identified and valued.

5. The Hidden Power of Social Networks - Rob Cross and Andrew Parker - Harvard Business Review Press (2004) - Chapter 5 covers cross-boundary collaboration patterns and how to detect and bridge organizational silos using network analysis, directly applicable to community detection interpretation.

6. Clustering Coefficient - Wikipedia - Measures the degree to which nodes in a graph tend to cluster together. High clustering coefficients indicate tightly-knit teams; low values suggest fragmented or loosely connected groups.

7. Cosine Similarity - Wikipedia - Explains the vector-based similarity measure used to compare employees based on feature profiles such as skills, communication patterns, or project involvement regardless of magnitude.

8. Label Propagation Algorithm - Wikipedia - Fast community detection method where nodes adopt the most frequent label among their neighbors. Useful for rapid exploratory analysis of organizational community structure.

9. Modularity (networks) - Wikipedia - Mathematical measure of how well a network decomposes into communities. Provides the objective function that algorithms like Louvain optimize when detecting organizational clusters.

10. Network Science - Chapter 9: Communities - Barabási Lab - Free online chapter covering community detection theory, algorithms, and the resolution limit problem. Provides mathematical foundation for understanding when communities are real vs. artifacts.