In a Competitive Market, Understanding Customer Demand and Effective Advertising is one of the most Important Factors in Survival. Extend the Internet and virtual networks have provided a great opportunity for companies to advertise, and thus studying electronic marketi
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In a Competitive Market, Understanding Customer Demand and Effective Advertising is one of the most Important Factors in Survival. Extend the Internet and virtual networks have provided a great opportunity for companies to advertise, and thus studying electronic marketing methods and models is of great importance. One of the newest marketing methods is viral marketing that is based on mouth-to-mouth advertising and has a lot of power. Viral marketing relies on the principle that on any social network, a number of users have high power and influence on others, and by identifying them and creating good advertising messages, They can be used to effectively marketing. Therefore, The identification of important users is considered the most important activity in viral marketing. In this regard, various studies have been conducted to identify users using a variety of graph-based and publish-based methods. In this research, the capabilities of both methods have been used and by Using a semi-localized centrality criterion based on graph-based methods and Markov clustering model based on propagation methods, a new hybrid model for user clustering and identification of key users presented. The results show higher correlation between the proposed method and the SIR standard and, therefore, its higher efficiency than other methods used in the research.
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