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A new hierarchical clustering algorithm to identify non-overlapping like-minded communities. / Deepak, Talasila Sai; Adhya, Hindol; Kejriwal, Shyamal; Gullapalli, Bhanuteja; Shannigrahi, Saswata.

HT 2016 - Proceedings of the 27th ACM Conference on Hypertext and Social Media. Association for Computing Machinery, 2016. p. 319-321 (HT 2016 - Proceedings of the 27th ACM Conference on Hypertext and Social Media).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Harvard

Deepak, TS, Adhya, H, Kejriwal, S, Gullapalli, B & Shannigrahi, S 2016, A new hierarchical clustering algorithm to identify non-overlapping like-minded communities. in HT 2016 - Proceedings of the 27th ACM Conference on Hypertext and Social Media. HT 2016 - Proceedings of the 27th ACM Conference on Hypertext and Social Media, Association for Computing Machinery, pp. 319-321, 27th ACM Conference on Hypertext and Social Media, HT 2016, Halifax, Canada, 10/07/16. https://doi.org/10.1145/2914586.2914613

APA

Deepak, T. S., Adhya, H., Kejriwal, S., Gullapalli, B., & Shannigrahi, S. (2016). A new hierarchical clustering algorithm to identify non-overlapping like-minded communities. In HT 2016 - Proceedings of the 27th ACM Conference on Hypertext and Social Media (pp. 319-321). (HT 2016 - Proceedings of the 27th ACM Conference on Hypertext and Social Media). Association for Computing Machinery. https://doi.org/10.1145/2914586.2914613

Vancouver

Deepak TS, Adhya H, Kejriwal S, Gullapalli B, Shannigrahi S. A new hierarchical clustering algorithm to identify non-overlapping like-minded communities. In HT 2016 - Proceedings of the 27th ACM Conference on Hypertext and Social Media. Association for Computing Machinery. 2016. p. 319-321. (HT 2016 - Proceedings of the 27th ACM Conference on Hypertext and Social Media). https://doi.org/10.1145/2914586.2914613

Author

Deepak, Talasila Sai ; Adhya, Hindol ; Kejriwal, Shyamal ; Gullapalli, Bhanuteja ; Shannigrahi, Saswata. / A new hierarchical clustering algorithm to identify non-overlapping like-minded communities. HT 2016 - Proceedings of the 27th ACM Conference on Hypertext and Social Media. Association for Computing Machinery, 2016. pp. 319-321 (HT 2016 - Proceedings of the 27th ACM Conference on Hypertext and Social Media).

BibTeX

@inproceedings{a07e6434292c477b8663eb5605c12034,
title = "A new hierarchical clustering algorithm to identify non-overlapping like-minded communities",
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.",
keywords = "Community detection, Like-mindedness, Modularity",
author = "Deepak, {Talasila Sai} and Hindol Adhya and Shyamal Kejriwal and Bhanuteja Gullapalli and Saswata Shannigrahi",
year = "2016",
month = jul,
day = "10",
doi = "10.1145/2914586.2914613",
language = "English",
series = "HT 2016 - Proceedings of the 27th ACM Conference on Hypertext and Social Media",
publisher = "Association for Computing Machinery",
pages = "319--321",
booktitle = "HT 2016 - Proceedings of the 27th ACM Conference on Hypertext and Social Media",
address = "United States",
note = "27th ACM Conference on Hypertext and Social Media, HT 2016 ; Conference date: 10-07-2016 Through 13-07-2016",

}

RIS

TY - GEN

T1 - A new hierarchical clustering algorithm to identify non-overlapping like-minded communities

AU - Deepak, Talasila Sai

AU - Adhya, Hindol

AU - Kejriwal, Shyamal

AU - Gullapalli, Bhanuteja

AU - Shannigrahi, Saswata

PY - 2016/7/10

Y1 - 2016/7/10

N2 - 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.

AB - 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.

KW - Community detection

KW - Like-mindedness

KW - Modularity

UR - http://www.scopus.com/inward/record.url?scp=84980319972&partnerID=8YFLogxK

U2 - 10.1145/2914586.2914613

DO - 10.1145/2914586.2914613

M3 - Conference contribution

AN - SCOPUS:84980319972

T3 - HT 2016 - Proceedings of the 27th ACM Conference on Hypertext and Social Media

SP - 319

EP - 321

BT - HT 2016 - Proceedings of the 27th ACM Conference on Hypertext and Social Media

PB - Association for Computing Machinery

T2 - 27th ACM Conference on Hypertext and Social Media, HT 2016

Y2 - 10 July 2016 through 13 July 2016

ER -

ID: 49849008