NDLI: Community detection in dynamic social networks: A game-theoretic approach

Content Provider	IEEE Xplore Digital Library
Author	Alvari, H. Hajibagheri, A. Sukthankar, G.
Copyright Year	2014
Description	Author affiliation: Dept. of EECS, Univ. of Central Florida, Orlando, FL, USA (Alvari, H.; Hajibagheri, A.; Sukthankar, G.)
Abstract	Most real-world social networks are inherently dynamic and composed of communities that are constantly changing in membership. As a result, recent years have witnessed increased attention toward the challenging problem of detecting evolving communities. This paper presents a game-theoretic approach for community detection in dynamic social networks in which each node is treated as a rational agent who periodically chooses from a set of predefined actions in order to maximize its utility function. The community structure of a snapshot emerges after the game reaches Nash equilibrium; the partitions and agent information are then transferred to the next snapshot. An evaluation of our method on two real world dynamic datasets (AS-Internet Routers Graph and AS-Oregon Graph) demonstrates that we are able to report more stable and accurate communities over time compared to the benchmark methods.
Starting Page	101
Ending Page	107
File Size	465095
Page Count	7
File Format	PDF
ISBN	9781479958771
DOI	10.1109/ASONAM.2014.6921567
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-17
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Social network services Heuristic algorithms Image edge detection Conferences Communities Games dynamic social networks Peer-to-peer computing game-theoretic models community detection
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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