Chinese whispers (clustering method)

<p>Chinese whispers is a clustering method used in network science named after the famous <a href="/facts/Chinese_whispers/lsQDLf5U">whispering game</a>. Clustering methods are basically used to identify communities of nodes or links in a given network. This algorithm was designed by Chris Biemann and Sven Teresniak in 2005. The name comes from the fact that the process can be modeled as a separation of communities where the nodes send the same type of information to each other.
</p><p>Chinese whispers is a hard partitioning, randomized, flat clustering (no <a href="/facts/Hierarchical_clustering/KxXs6GPK">hierarchical relations between clusters</a>) method. The random property means that running the process on the same network several times can lead to different results, while because of hard partitioning one node can belong to only one cluster at a given moment. The original algorithm is applicable to undirected, weighted and unweighted graphs. Chinese whispers runs in linear time, which means that it is extremely fast even if there are very many nodes and links in the network.
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Chinese whispers (clustering method) open-in-new

Chinese whispers (clustering method)