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Synchronous-Louvain

Created by Hong Huang (Master thesis) This repository contains the code for synchronous Louvain community detection algorithm.

To demonstrate how this algorithm works, here is a toy example: The toy example

The numbers inside the circle are vertice id and all the other numbers are edge weights. I have added self loop on purpose to verify the correctness of the program. The weight of selft loop is twice the weight of the community that the current node represents. For instance, you can see that node 3 has a self loop of weight 1.0, so the community in the previous level that node 3 represents has a total internal weight of 0.5, 0.5x2=1.

#Initial Setting Initially, every node is in his own community. The total weight of edges in this graph is 12, so m is 12, 2m is 24.

##Sigma Tot For node 3, the sum of the weights of the links incident to nodes in the community(sigma tot for community 3) is 4.0.

For node 5, the sum of the weights of the links incident to nodes in the community(sigma tot for community 5) is 10.0.

For node 7, the sum of the weights of the links incident to nodes in the community(sigma tot for community 7) is 6.0.

For node 2, the sum of the weights of the links incident to nodes in the community(sigma tot for community 2) is 4.0.

##Adjacent Weights (k_i) The sum of the weights of the links incident to node 3 is 1.0+1.0+2.0=4.0, so k_i=4.0 for node 3.

The sum of the weights of the links incident to node 7 is 1.0+1.0+4.0=6.0, so k_i=6.0 for node 7.

The sum of the weights of the links incident to node 2 is 1.0+3.0=4.0, so k_i=4.0 for node 2.

The sum of the weights of the links incident to node 5 is 1.0+3.0+4.0+2.0=10.0, so k_i=10.0 for node 5.

##Choice of community

###For node 3:

If he stays in the current community, the gain is 0 because you are doing nothing(removing a node from the community of its own and then add it to the community of its own). If he joins community 7, the weight from community 7 to node 3 is 1.0, so k_i_in is 1.0, the gain of modularity(ignore the scalar 1/2m) is k_i_in-(sima_totk_i)/m=1.0-(6.04.0)/12=-1.0<0.

If he joins community 5, the weight from community 5 to node 3 is 2.0, so k_i_in is 2.0. The gain of modularity(ignore the scalar 1/2m) is k_i_in-(sima_totk_i)/m=2.0-(10.04.0)/12=2.0-10/3=-4/3<0.

So node 3 should stay in his original community.

###For node 5:

If he stays in the current community, the gain is 0 because you are doing nothing(removing a node from the community of its own and then add it to the community of its own). If he joins community 3, the weight from community 3 to node 5 is 2.0, so k_i_in is 2.0, the gain of modularity(ignore the scalar 1/2m) is k_i_in-(sima_totk_i)/m=2.0-(4.010.0)/12=2-10/3=-4/3<0.

If he joins community 7, the weight from community 7 to node 5 is 4.0, so k_i_in is 4.0. The gain of modularity(ignore the scalar 1/2m) is k_i_in-(sima_totk_i)/m=4.0-(6.010.0)/12=-1<0.

If he joins community 2, the weight from community 2 to node 5 is 3.0, so k_i_in is 3.0. The gain of modularity(ignore the scalar 1/2m) is k_i_in-(sima_totk_i)/m=3.0-(4.010.0)/12=3-10/3=-1/3<0.

So node 5 should stay in his original community.

###For node 7:

If he stays in the current community, the gain is 0 because you are doing nothing(removing a node from the community of its own and then add it to the community of its own). If he joins community 3, the weight from community 3 to node 7 is 1.0, so k_i_in is 1.0, the gain of modularity(ignore the scalar 1/2m) is k_i_in-(sima_totk_i)/m=1.0-(4.06.0)/12=-1<0.

If he joins community 5, the weight from community 5 to node 7 is 4.0, so k_i_in is 4.0. The gain of modularity(ignore the scalar 1/2m) is k_i_in-(sima_totk_i)/m=4.0-(10.06.0)/12=-1<0.

So node 7 should stay in his original community.

###For node 2:

If he stays in the current community, the gain is 0 because you are doing nothing(removing a node from the community of its own and then add it to the community of its own). If he joins community 5, the weight from community 5 to node 2 is 3.0, so k_i_in is 3.0, the gain of modularity(ignore the scalar 1/2m) is k_i_in-(sima_totk_i)/m=3.0-(10.04.0)/12=3-10/3=-1/3. Smaller than 0.

So node 2 should stay in his original community

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