DECS

Implementation of "Detecting the Evolving Community Structure in Dynamic Social Networks".

If you find this method helpful for your research, please cite this paper.

@Article{Liu2019, 
	author = {Fanzhen Liu and Jia Wu and Shan Xue and Chuan Zhou and Jian Yang and Quanzheng Sheng},
	journal = {World Wide Web},
	title = {Detecting the Evolving Community Structure in Dynamic Social Networks},
	year = {2020},
	volume = {23},
	pages = {715-733},
	doi = {10.1007/s11280-019-00710-z}
}

Requirement

Matlab >= 2013a

Datasets

Datasets used in this paper can be obtain from the original sources.

Dataset		Source
Synthetic datasets	SYN-FIX	M.-S. Kim and J. Han, “A particle-and-density based evolutionary clustering method for dynamic networks,” Proc. VLDB Endow., vol. 2, no. 1, pp. 622–633, 2009.
	SYN-VAR
	SYN-EVENT	D. Greene, D. Doyle, and P. Cunningham, “Tracking the evolution of communities in dynamic social networks,” in Proc. Int. Conf. Adv. Soc. Netw. Anal. Min. (ASONAM), pp. 176–183, 2010.
Real-world datasets	Cellphone Calls	http://www.cs.umd.edu/hcil/VASTchallenge08/
Real-world datasets	Enron Mail	http://www.cs.cmu.edu/~enron/

How to use

Before run the run_DECS.m, please choose a network to load and properly set corresponding parameters in the run_DECS.m. Please see the content in run_DECS.m for more information.

The W_Cube.mat records the adjacent matrices of a dynamic network in several time steps, the GT_Cube.mat or GT_Matrix.mat records the ground truth community structures of a synthetic network in all time steps. For Real-world networks without ground truth community structures, the firststep_DYNMOGA_cell.mat and firststep_DYNMOGA_enron.mat record the community structures detected by the first step of DYNMOGA (Folino and Pizzuti 2014) in all timesteps as the ground truth community structures.

Finally, DECS_Result records the community structures detected by DECS in all time steps; DynMod and DynNmi record the modularity of the detected community structure at each time step and the NMI that measures the similarity between a detected community structure and the ground truth at each time step, respectively.

Disclaimer

If you find any bugs, please report them to me.

FanzhenLiu/DECS

DECS