Title :
On Measuring the Quality of a Network Community Structure
Author :
Mingming Chen ; Nguyen, Thin ; Szymanski, Boleslaw K.
Author_Institution :
Dept. of Comput. Sci., Rensselaer Polytech. Inst., Troy, NY, USA
Abstract :
Modularity is widely used to effectively measure the strength of the community structure found by community detection algorithms. However, modularity maximization suffers from two opposite yet coexisting problems: in some cases, it tends to favor small communities over large ones while in others, large communities over small ones. The latter tendency is known in the literature as the resolution limit problem. To address them, we propose to modify modularity by subtracting from it the fraction of edges connecting nodes of different communities and by including community density into modularity. We refer to the modified metric as Modularity Density and we demonstrate that it indeed resolves both problems mentioned above. We describe the motivation for introducing this metric by using intuitively clear and simple examples. We also discuss the results of applying this metric, modularity, and several other popular community quality metrics to two real dynamic networks. The results imply that Modularity Density is consistent with all the community quality measurements but not modularity, which suggests that Modularity Density is an improved measurement of the community quality compared to modularity.
Keywords :
network theory (graphs); optimisation; community density; community detection algorithms; community quality metrics; modularity density; modularity maximization; network community structure quality; real dynamic networks; resolution limit problem; Bluetooth; Communities; Data mining; Density measurement; Heuristic algorithms; Image edge detection; Community Detection; Community Quality Metric; Modularity; Resolution Limit;
Conference_Titel :
Social Computing (SocialCom), 2013 International Conference on
Conference_Location :
Alexandria, VA
DOI :
10.1109/SocialCom.2013.25