A density-based approach for mining overlapping communities from social network interactions

Sajid Yousuf Bhat, Muhammad Abulaish
2012 Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics - WIMS '12  
In this paper, we propose a density-based community detection method, CMiner, which exploits the interaction graph of online social networks to identify overlapping community structures. Based on the average reciprocated interactions of a node in the network, a new distance function is defined to find the similarity between a pair of nodes. The proposed method also provides a basic solution for automatic determination of the neighborhood threshold, which is a non-trivial problem for applying
more » ... sity-based clustering methods. Considering the local neighborhood of a node p, the distance function is used to determine the distance between the node p and its neighbors in the interaction graph to identify core nodes, which are then used to define overlapping communities. On comparing the experimental results with clique percolation and other related methods, we found that CMiner is comparable to the state-of-the-art methods and is also computationally faster.
doi:10.1145/2254129.2254143 dblp:conf/wims/BhatA12 fatcat:k3gakh4a3zdzzaolyqqfsfcywe