Title of article
Discovering groups of key potential customers in social networks: A multi-objective optimization model
Author/Authors
Hamidihesarsorkh, Aghil School of progress Engineering - Iran university science and technology , Papi, Ali School of progress Engineering - Iran university science and technology , Bonyadi Naeini, Ali School of progress Engineering - Iran university science and technology , Jabarzadeh, Armin School of progress Engineering - Iran university science and technology
Pages
11
From page
85
To page
95
Abstract
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
Keywords
Social network analysis , Influence Maximization , diffusion Speed , Multi-objective optimization
Journal title
International Journal of Industrial Engineering and Production Research
Serial Year
2017
Record number
2504589
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