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Editorial Team
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Editorial Team
Asked: May 20, 20262026-05-20T03:06:10+00:00 2026-05-20T03:06:10+00:00

I am familiar with various clustering algorithms (k-means etc) but for my specific use

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I am familiar with various clustering algorithms (k-means etc) but for my specific use case (social networks), I need an algorithm that detects overlapping groups. This algorithm neatly separates my Facebook friends into my high school friends, my college friends, my family and my work friends.

The algorithm I used above (JUNG’s VoltageClusterer) separates nodes into single clusters. But I want an algorithm that can assign nodes multiple clusters (e.g. a friend of mine can be both my high school friend and college friend).

How do I do this? It would be nice if I can have this algorithm work for weighted graphs too instead of just unweighted ones.

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  1. Editorial Team
    Editorial Team
    2026-05-20T03:06:10+00:00Added an answer on May 20, 2026 at 3:06 am

    Palla et al have a nice Nature paper on detecting overlapping communities:
    http://www.nature.com/nature/journal/v435/n7043/full/nature03607.html
    They demonstrate its success in different types of networks, from social to protein interaction.

    The algorithm is called k-clique percolation. It’s implemented in their C-finder program:
    http://www.cfinder.org/

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