Algorithm 2 Node enthusiasm measurement based on the GN algorithm
Input: G
Output: Q, communitymax
1:		while len(G.edges()) > 0 do  //Determine whether any node in the graph is a community
2:		edge = max(edge_betweenness(G))    //Find the edge with the largest edge betweenness in the graph
3:		G.remove_edge(edge[0], edge[1])      //Remove the edges with the largest edge betweenness
4:		components = connected_components(G)    //The connected subgraph is obtained after removing the edges
5:		if len(components)! = len(nodes):      //Determine whether any node of the connected subgraph is a community
6:		Q, community = cal_Q(components, G) //Calculate the modularity metric value Q
7:		if Qn > Qmax: //Determine whether the sum Qn of Q values is maximum
8:		Q, Qmax, communitymax = Q, Qn, community //Record the communities that are now formed, Q and Qn
9:		end if
10:		end if
11:		end while
12:		return Q, communitymax