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Adding short description: "Community detection algorithm" (Shortdesc helper) |
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# The edge(s) with the highest betweenness are removed.
# The betweenness of all edges affected by the removal is recalculated.
# Steps 2 and 3 are repeated until no edges remain
The fact that the only betweennesses being recalculated are only the ones which are affected by the removal, may lessen the running time of the process' simulation in computers. However, the betweenness centrality must be recalculated with each step, or severe errors occur. The reason is that the network adapts itself to the new conditions set after the edge removal. For instance, if two communities are connected by more than one edge, then there is no guarantee that '''all''' of these edges will have high betweenness. According to the method, we know that '''at least one''' of them will have, but nothing more than that is known. By recalculating betweennesses after the removal of each edge, it is ensured that at least one of the remaining edges between two communities will always have a high value.
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