Influence maximization in social networks under an independent cascade-based model

Qiyao Wang, Yuehui Jin, Zhen Lin, Shiduan Cheng and Tan Yang

Physica A: Statistical Mechanics and its Applications, 2016, vol. 444, issue C, 20-34

Abstract: The rapid growth of online social networks is important for viral marketing. Influence maximization refers to the process of finding influential users who make the most of information or product adoption. An independent cascade-based model for influence maximization, called IMIC-OC, was proposed to calculate positive influence. We assumed that influential users spread positive opinions. At the beginning, users held positive or negative opinions as their initial opinions. When more users became involved in the discussions, users balanced their own opinions and those of their neighbors. The number of users who did not change positive opinions was used to determine positive influence. Corresponding influential users who had maximum positive influence were then obtained. Experiments were conducted on three real networks, namely, Facebook, HEP-PH and Epinions, to calculate maximum positive influence based on the IMIC-OC model and two other baseline methods. The proposed model resulted in larger positive influence, thus indicating better performance compared with the baseline methods.

Keywords: Influence maximization; Positive influence; Independent cascade-based model; Opinion change; Social networks (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:444:y:2016:i:c:p:20-34

DOI: 10.1016/j.physa.2015.10.020

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