Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/2037
Title: An evolutionary approach for detecting communities in social networks
Authors: Öztürk, K.
Polat, F.
Özyer, Tansel
143116
Keywords: Algorithms 
 Population dynamics 
 detect communities
Issue Date: 31-Jul-2017
Publisher: Association for Computing Machinery, Inc.
Source: Ozturk, K., Polat, F., & Ozyer, T. (2017, July). An Evolutionary Approach for Detecting Communities in Social Networks. In Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017 (pp. 966-973). ACM.
Abstract: Rapid development and wide usage of social networking applications have enabled large amounts of valuable data which can be analyzed for various reasons by companies, governments, non-profit organizations such as UN. This paper presents an evolutionary approach for detecting communities in social networks. We formulated a genetic algorithm that does not require the number of communities as input and is able to detect communities effectively in a very fast way. The performance of the proposed method is compared to its counterparts in order to show that good results can be generated. Additionally, we have done experiments using Newman’s Spectral Clustering Method as a pre-processing step and it gave much better results. © 2017 Association for Computing Machinery.
Description: 9th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (2017 : Sydney; Australia)
URI: https://dl.acm.org/citation.cfm?doid=3110025.3110157
https://hdl.handle.net/20.500.11851/2037
ISBN: 978-145034993-2
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Show full item record

CORE Recommender

SCOPUSTM   
Citations

3
checked on Sep 23, 2022

Page view(s)

20
checked on Dec 26, 2022

Google ScholarTM

Check

Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.