TY - JOUR A2 - Musial, Katarzyna AU - Narantsatsralt, Ulzii-Utas AU - Kang, Sanggil PY - 2017 DA - 2017/11/07 TI - Social Network Community Detection Using Agglomerative Spectral Clustering SP - 3719428 VL - 2017 AB - Community detection has become an increasingly popular tool for analyzing and researching complex networks. Many methods have been proposed for accurate community detection, and one of them is spectral clustering. Most spectral clustering algorithms have been implemented on artificial networks, and accuracy of the community detection is still unsatisfactory. Therefore, this paper proposes an agglomerative spectral clustering method with conductance and edge weights. In this method, the most similar nodes are agglomerated based on eigenvector space and edge weights. In addition, the conductance is used to identify densely connected clusters while agglomerating. The proposed method shows improved performance in related works and proves to be efficient for real life complex networks from experiments. SN - 1076-2787 UR - https://doi.org/10.1155/2017/3719428 DO - 10.1155/2017/3719428 JF - Complexity PB - Hindawi KW - ER -