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Identifying Hesitant and Interested Customers for Targeted Social Marketing

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Abstract

Social networks provide unparalleled opportunities for marketing products or services. Along this line, tremendous efforts have been devoted to the research of targeted social marketing, where the marketing efforts could be concentrated on a particular set of users with high utilities. Traditionally, these targeted users are identified based on their potential interests to the given company (product). However, social users are usually influenced simultaneously by multiple companies, and not only the user interest but also these social influences will contribute to the user consumption behaviors. To that end, in this paper, we propose a general approach to figure out the targeted users for social marketing, taking both user interests and multiple social influences into consideration. Specifically, we first formulate it as an Identifying Hesitant and Interested Customers (IHIC) problem, where we argue that these valuable users should have the best balanced influence entropy (being “Hesitant”) and utility scores (being “Interested”). Then, we design a novel framework and propose specific algorithms to solve this problem. Finally, extensive experiments on two real-world datasets validate the effectiveness and the efficiency of our proposed approach.

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Correspondence to Qi Liu .

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Ma, G., Liu, Q., Wu, L., Chen, E. (2015). Identifying Hesitant and Interested Customers for Targeted Social Marketing. In: Cao, T., Lim, EP., Zhou, ZH., Ho, TB., Cheung, D., Motoda, H. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2015. Lecture Notes in Computer Science(), vol 9077. Springer, Cham. https://doi.org/10.1007/978-3-319-18038-0_45

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  • DOI: https://doi.org/10.1007/978-3-319-18038-0_45

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18037-3

  • Online ISBN: 978-3-319-18038-0

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