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2015 | OriginalPaper | Buchkapitel

Evolutionary Influence Maximization in Viral Marketing

verfasst von : Sanket Anil Naik, Qi Yu

Erschienen in: Recommendation and Search in Social Networks

Verlag: Springer International Publishing

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Abstract

With the growth of social networks, significant amount of data is brought online that can benefit applications of many kinds if being effectively utilized. As a typical example, Domnigos proposed the concept of viral marketing, which uses the “word of mouth” marketing technique over virtual networks (Domingos, IEEE Intell Syst 20:80–82, 2005). Each user is associated with a network value that represents his/her influence in the network. The network value is used along with other intrinsic features that represent user shopping behaviors for the selection of a small subset of most influential users in the network for marketing purpose. However, most existing viral marketing techniques ignore the dynamic nature of the virtual network where both the features and the relationship of users may change over time. In this paper, we develop a novel framework for the selection of users by exploiting the temporal dynamics of the network. Incorporating temporal dynamics of the network would assist in selecting an optimal subset of users with the maximum influence over the network. This paper focuses on developing an algorithm for the selection of the users to market the product by exploiting the temporal and the structural dynamics of the network. Extensive experimental results over real-world datasets clearly demonstrate the effectiveness of the proposed framework.

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Metadaten
Titel
Evolutionary Influence Maximization in Viral Marketing
verfasst von
Sanket Anil Naik
Qi Yu
Copyright-Jahr
2015
DOI
https://doi.org/10.1007/978-3-319-14379-8_11

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