標題: Using a two-phase evolutionary framework to select multiple network spreaders based on community structure
作者: Fu, Yu-Hsiang
Huang, Chung-Yuan
Sun, Chuen-Tsai
資訊工程學系
Department of Computer Science
關鍵字: Genetic algorithm;Community detection;Network spreading;Social network analysis;Multiple network spreaders
公開日期: 1-十一月-2016
摘要: Using network community structures to identify multiple influential spreaders is an appropriate method for analyzing the dissemination of information, ideas and infectious diseases. For example, data on spreaders selected from groups of customers who make similar purchases may be used to advertise products and to optimize limited resource allocation. Other examples include community detection approaches aimed at identifying structures and groups in social or complex networks. However, determining the number of communities in a network remains a challenge. In this paper we describe our proposal for a two-phase evolutionary framework (TPEF) for determining community numbers and maximizing community modularity. Lancichinetti-Fortunato-Radicchi benchmark networks were used to test our proposed method and to analyze execution time, community structure quality, convergence, and the network spreading effect. Results indicate that our proposed TPEF generates satisfactory levels of community quality and convergence. They also suggest a need for an index, mechanism or sampling technique to determine whether a community detection approach should be used for selecting multiple network spreaders. (C) 2016 Elsevier B.V. All rights reserved.
URI: http://dx.doi.org/10.1016/j.physa.2016.06.042
http://hdl.handle.net/11536/134053
ISSN: 0378-4371
DOI: 10.1016/j.physa.2016.06.042
期刊: PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
Volume: 461
起始頁: 840
結束頁: 853
顯示於類別:期刊論文