In this paper, a simple but efficient method of overlapping community detection is presented using local community gravitation in social networks. Given a highquality, non-overlapping partition generated by existing methods, this proposed method identifies the overlapping nodes from their surrounding partitioned communities according to their local community gravitation, with low computational ...

A hierarchical overlapping community discovery algorithm based on node purity (OCFN-PN) is proposed in the paper. This algorithm chooses the maximal relative centrality as the initial community, which solves the problem of inconsistent results of the community discovery algorithm based on fitness resulting from randomly choosing nodes. Before optimizing and merging communities, the community ov...

Identification of (overlapping) communities/clusters in a complex network is a general problem in data mining of network data sets. In this paper, we devise a novel algorithm to identify overlapping communities in complex networks by the combination of a new modularity function based on generalizing NG’s Q function, an approximation mapping of network nodes into Euclidean space and fuzzy c-mean...

---------------------------------------------------------------------***--------------------------------------------------------------------Abstract Community detection in a Social network is a trending issue in the study of network system and it helps to realize and study the overall network structure in detail. Communities are basically the partition of network nodes into some subgroups in wh...

Complex networks is an interdisciplinary research area getting attention from a variety of disciplines including sociology, biology, and computer science. It studies the properties of complex systems that may have many functional or structural subunits. Community detection algorithms are one of the major approaches to analyse complex networks by finding these intermediate-level subunits called ...

The advent of social networks poses severe threats on user privacy as adversaries can de-anonymize users’ identities by mapping them to correlated cross-domain networks. Without ground-truth mapping, prior literature proposes various cost functions in hope of measuring the quality of mappings. However, there is generally a lacking of rationale behind the cost functions, whose minimizer also rem...

Previous studies on social networks are often focused on networks with only positive relations between individual nodes. As a significant extension, we conduct the spectral analysis on graphs with both positive and negative edges. Specifically, we investigate the impacts of introducing negative edges and examine patterns in the spectral space of the graph’s adjacency matrix. Our theoretical res...

Community detection and overlapping community detection has been of significant importance in the last decade wherein invention and growth of social networks like Facebook, Twitter, Linkedin, Flickr, etc. has even made it more crucial to investigate better approaches. Overlapping community detection has many application as in modern market analysis and recommendation systems, bioinformatic syst...

With greater availability of data and increasing interaction activities taking place on social media, detecting overlapping and hierarchical communities has become an important issue and one that is essential to social media analysis. In this paper, we propose a coalition formation game theory-based approach to identify overlapping and hierarchical communities. We model community detection as a...

The investigation of network structure has important significance to understand the functions of various complex networks. The communities with hierarchical and overlapping structures and the special nodes like hubs and outliers are all common structure features to the networks. Network structure investigation has attracted considerable research effort recently. However, existing studies have o...