A Constrained Louvain Algorithm with a Novel Modularity
Source abstract
Abstract
Community detection is a significant and challenging task in network research. Nowadays, many community detection methods have been developed. Among them, the classical Louvain algorithm is an excellent method aiming at optimizing an objective function. In this paper, we propose a modularity function F2 as a new objective function. Our modularity function F2 overcomes certain disadvantages of the modularity functions raised in previous literature, such as the resolution limit problem. It is desired as a competitive objective function. Then, the constrained Louvain algorithm is proposed by adding some constraints to the classical Louvain algorithm. Finally, through the comparison, we have found that the constrained Louvain algorithm with F2 is better than the constrained Louvain algorithm with other objective functions on most considered networks. Moreover, the constrained Louvain algorithm with F2 is superior to the classical Louvain algorithm and the Newman’s fast method.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Complex Network Analysis Techniques · Opinion Dynamics and Social Influence · Human Mobility and Location-Based Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mathematics and Physics, Southwest University of Science and Technology, Mianyang 621010, China
References (58)
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