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A New Hierarchical Clustering Algorithm to Identify Non-overlapping Like-minded Communities

Publication Type : Conference Paper

Publisher : ACM Conference on Hypertext and Social Media (HT),

Source : Proc. 27th ACM Conference on Hypertext and Social Media (HT)

Url : https://dl.acm.org/doi/abs/10.1145/2914586.2914613

Campus : Coimbatore

Year : 2016

Abstract : In this paper, we present a new algorithm to identify non-overlapping like-minded communities in a social network and compare its performance with Girvan-Newman algorithm, Lovain method and some well-known hierarchical clustering algorithms on Twitter and Filmtipset datasets.

Cite this Research Publication : T. S. Deepak, H. Adhya, S. Kejriwal, B. Gullapalli and S. Shannigrahi. A New Hierarchical Clustering Algorithm to Identify Non-overlapping Like-minded Communities. Proc. 27th ACM Conference on Hypertext and Social Media (HT), 319-321, 2016.

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