## 22.3. Deprecated: Community Detection via Label Propagation

This section describes the Label Propagation community detection algorithm.

| Graph Algorithms (similarity, centrality and clustering) in APOC are deprecated and about to be removed. Please use the algorithms in the Graph Algorithms Library instead.

APOC includes a simple procedure for label propagation. It may be used to detect communities or solve other graph partitioning problems. The following example shows how it may be used.

The example call with scan all nodes 25 times. During a scan the procedure will look at all outgoing relationships of type :X for each node n. For each of these relationships, it will compute a weight and use that as a vote for the other node’s 'partition' property value. Finally, n.partition is set to the property value that acquired the most votes.

Weights are computed by multiplying the relationship weight with the weight of the other nodes. Both weights are taken from the 'weight' property; if no such property is found, the weight is assumed to be 1.0. Similarly, if no 'weight' property key was specified, all weights are assumed to be 1.0.

    CALL apoc.algo.community(25,null,'partition','X','OUTGOING','weight',10000)

The second argument is a list of label names and may be used to restrict which nodes are scanned.