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Influence maximization in social networks aims to identify a set of key users who can effectively spread information or influence across the network. However, selecting influential users often involves high computational complexity and cost. This paper presents PP Rank, an economic and efficient approach for selecting initial users to maximize influence spread while minimizing resource usage. The proposed method prioritizes potential users based on propagation probability, network structure, and interaction strength, allowing for balanced trade-offs between influence gain and selection cost. By integrating probabilistic modeling and ranking algorithms, PP Rank identifies a cost-effective subset of users that ensures wide information diffusion. Experimental evaluations on real-world social network datasets demonstrate that PP Rank achieves near-optimal influence coverage with significantly reduced computational time compared to traditional greedy or heuristic-based methods. This study contributes to the design of scalable, economical influence maximization strategies applicable in viral marketing, information dissemination, and social recommendation systems.
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Copyright © 2020, This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC-BY-NY-SA). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Corresponding Author: K. Kantha Raju, kanakaraju8@gmail.com
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Conflict of interest: The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
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