IEEE Transactions on Knowledge and Data Engineering

IEEE Transactions on Knowledge and Data Engineering (TKDE) is an archival journal published monthly designed to inform researchers, developers, managers, strategic planners, users, and others interested in state-of-the-art and state-of-the-practice activities in the knowledge and data engineering area. Read the full scope of TKDE

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From the June 2018 issue

Profit Maximization for Viral Marketing in Online Social Networks: Algorithms and Analysis

By Jing Tang, Xueyan Tang, and Junsong Yuan

Featured Article Information can be disseminated widely and rapidly through Online Social Networks (OSNs) with “word-of-mouth” effects. Viral marketing is such a typical application in which new products or commercial activities are advertised by some seed users in OSNs to other users in a cascading manner. The selection of initial seed users yields a tradeoff between the expense and reward of viral marketing. In this paper, we define a general profit metric that naturally combines the benefit of influence spread with the cost of seed selection in viral marketing. We carry out a comprehensive study on finding a set of seed nodes to maximize the profit of viral marketing. We show that the profit metric is significantly different from the influence metric in that it is no longer monotone. This characteristic differentiates the profit maximization problem from the traditional influence maximization problem. We develop new seed selection algorithms for profit maximization with strong approximation guarantees. We also derive several upper bounds to benchmark the practical performance of an algorithm on any specific problem instance. Experimental evaluations with real OSN datasets demonstrate the effectiveness of our algorithms and techniques.

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Editorials and Announcements


  • TKDE now offers authors access to Code Ocean. Code Ocean is a cloud-based executable research platform that allows authors to share their algorithms in an effort to make the world’s scientific code more open and reproducible. Learn more or sign up for free.
  • We are pleased to announce that Xuemin Lin, a Scientia Professor in the School of Computer Science and Engineering at the University of New South Wales, Australia, has been named the new Editor-in-Chief of the IEEE Transactions on Knowledge and Data Engineering starting in 2017.


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