Volume 28, Number 1 (IJIEPR 2017)                   IJIEPR 2017, 28(1): 85-95 | Back to browse issues page



DOI: 10.22068/ijiepr.28.1.85

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Hamidihesarsorkh A, Papi A, Bonyadi Naeini A, Jabarzadeh A. Discovering groups of key potential customers in social networks: A multi-objective optimization model. IJIEPR. 2017; 28 (1) :85-95
URL: http://ijiepr.iust.ac.ir/article-1-744-en.html

Assistant Professor Iran university science and technology , Bonyadi@iust.ac.ir
Abstract:   (261 Views)

Nowadays, the popularity of social networks as marketing tools has brought a deal of attention to social networks analysis (SNA). One of the well-known Problems in this field is influence maximization problems which related to flow of information within networks. Although, the problem have been considered by many researchers, the concept behind of this problem has been used less in business context. In this paper, by using a cost-benefits analysis, we propose a multi-objective optimization model which helps to identify the key nodes location, which are a symbol of potential influential customers in real social networks. The main novelty of this model is that it determines the best nodes by combining two essential and realistic elements simultaneously: diffusion speed and dispersion cost. Also, the performance of the proposed model is validated by detecting key nodes on a real social network

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Highlights

  • A multi-objective model for identifying seed customers in social networks is proposed.
  • The exact model is a tradeoff between diffusion speed and dispersion cost.
  • Influence propagation is modeled as a multi-period process.

Type of Study: Research | Subject: E-Business and E-Commerce
Received: 2017/05/1 | Accepted: 2017/06/11 | Published: 2017/06/18

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