Revealing consensus and dissensus between network partitions

Understand

Community detection methods attempt to divide a network into groups of nodes that share similar properties, thus revealing its large-scale structure.

• A major challenge when employing such methods is that they are often degenerate, typically yielding a complex landscape of competing answers.
• As an attempt to extract understanding from a population of alternative solutions, many methods exist to establish a consensus among them in the form of a single partition "point estimate" that summarizes the whole distribution.
• Here we show that it is in general not possible to obtain a consistent answer from such point estimates when the underlying distribution is too heterogeneous.