Algorithm 1: LPA.

Input:$G=(V,E)$

Output: The result of community detection

1:Initializaion: assign a unique label to each node in the network, $C_x\left(0\right)=x$ 2:Set t=1 3:Arrange nodes in random order and set it to X. 4:Select each node x in the X sequentially and update its label according to the following function, $C_x\left(t\right)=f(C_{x_{i1}}\left(t\right),\dots ,C_{x_{im}}\left(t\right),C_{x_{i(m+1)}}(t-1),\dots ,C_{x_{ik}}(t-1))$, where $x_{i1},\dots ,x_{im}$ are the neighbors that have been updated before time t, and $x_{i(m+1)},\dots ,x_{ik}$ are the neighbors that have not been updated before time t. 5:If the label in network no longer changes, stop the algorithm, else set $t=t+1$ and go to step 3.