Evaluating Local Community Methods in Networks

Abstract

We present a new benchmarking procedure that is unambiguous and specific to local community-finding methods, allowing one to compare the accuracy of various methods. We apply this to new and existing algorithms. A simple class of synthetic benchmark networks is also developed, capable of testing properties specific to these local methods.

8 pages, 9 figures, code included with source

References in corpus (24)

• Statistical mechanics of complex networks
• The structure and function of complex networks
• Community structure in social and biological networks
• Finding and evaluating community structure in networks
• Modularity and community structure in networks
• Finding community structure in very large networks
• Fast algorithm for detecting community structure in networks
• Uncovering the overlapping community structure of complex networks in nature and society
• The large-scale organization of metabolic networks
• Resolution limit in community detection
• Comparing community structure identification
• Defining and identifying communities in networks
• Statistical Mechanics of Community Detection
• Quantifying social group evolution
• CFinder: Locating cliques and overlapping modules in biological networks
• Modularity from Fluctuations in Random Graphs and Complex Networks
• Finding local community structure in networks
• Clique percolation in random networks
• Pattern Detection in Complex Networks: Correlation Profile of the Internet
• A Local Method for Detecting Communities
• Local modularity measure for network clusterizations
• Identifying "communities" within energy landscapes
• Community structure and ethnic preferences in school friendship networks
• The critical point of k-clique percolation in the Erdos-Renyi graph

Cited by in corpus (30)

• Community detection in graphs
• Link communities reveal multiscale complexity in networks
• The performance of modularity maximization in practical contexts
• A Comparative Analysis of Community Detection Algorithms on Artificial Networks
• An efficient and principled method for detecting communities in networks
• Community landscapes: an integrative approach to determine overlapping network module hierarchy, identify key nodes and predict network dynamics
• Think Locally, Act Locally: The Detection of Small, Medium-Sized, and Large Communities in Large Networks
• Spectral methods for the detection of network community structure: a comparative analysis
• Communities and bottlenecks: Trees and treelike networks have high modularity
• Block Models and Personalized PageRank
• Qualitative Comparison of Community Detection Algorithms
• Covariance, correlation matrix and the multi-scale community structure of networks
• Communities in Networks
• Towards realistic artificial benchmark for community detection algorithms evaluation
• Multi-resolution community detection based on generalized self-loop rescaling strategy
• Hierarchical benchmark graphs for testing community detection algorithms
• Efficient local behavioral change strategies to reduce the spread of epidemics in networks
• Enhancing community detection by local structural information
• On Accuracy of Community Structure Discovery Algorithms
• Community detection by spectral methods in multi-layer networks
• Seeding for pervasively overlapping communities
• Community detection based on significance optimization in complex networks
• Community detection for weighted bipartite networks
• Partition of Networks into Basins of Attraction
• Contrarian effects and echo chamber formation in opinion dynamics
• Non-overlapping community detection
• Self-falsifiable Hierarchical Detection of Overlapping Communities On Social Networks
• The Atlas for the Aspiring Network Scientist
• Metrics for Community Analysis: A Survey
• Evaluating community structure in large network with random walks