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Analysis of Communities Detection Algorithms in Complex Networks

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Moises Bruno L. Bissoto, Ary Henrique M. Oliveira, Glenda M. Botelho

Moises Bruno L Bissoto, Ary Henrique M Oliveira and Glenda M Botelho. Analysis of Communities Detection Algorithms in Complex Networks. International Journal of Computer Applications 173(7):1-7, September 2017. BibTeX

	author = {Moises Bruno L. Bissoto and Ary Henrique M. Oliveira and Glenda M. Botelho},
	title = {Analysis of Communities Detection Algorithms in Complex Networks},
	journal = {International Journal of Computer Applications},
	issue_date = {September 2017},
	volume = {173},
	number = {7},
	month = {Sep},
	year = {2017},
	issn = {0975-8887},
	pages = {1-7},
	numpages = {7},
	url = {},
	doi = {10.5120/ijca2017915356},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Complex networks are an imminent multidisciplinary field defined by graphs that present a nontrivial topographic structure. An important information extracted from a complex network is its communities structure. In the literature, there are several communities detection algorithms, however, new research have emerged with the aim of detecting communities efficiently and with lower computational cost. Therefore, this work analyzes different algorithms for communities detection in complex networks with different characteristics, considering the Modularity measure, the execution time and the obtained communities number. The partitions obtained by the different algorithms presented high modularity values and it was observed that the influence of the number of vertices and edges in the execution time of some detection algorithms.


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Complex networks, Community detection algorithms, Modularity measure, Evaluation