Competitive Influence Maximization with Uncertain Competitor Sources and the Bandwagon Effect in Social Networks

Tao Sun (), Suning Gong (), Guo-Qiang Fan and Gongjie Xu ()
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Tao Sun: Department of Industrial Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, P. R. China
Suning Gong: School of Mathematical Science, Ocean University of China, Qingdao 266100, P. R. China
Guo-Qiang Fan: Department of Management Science and Engineering, School of Economics and Management, Xidian University, Xi’an, Shaanxi 710126, P. R. China
Gongjie Xu: Department of Industrial Engineering, School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, P. R. China

Asia-Pacific Journal of Operational Research (APJOR), 2024, vol. 41, issue 05, 1-26

Abstract: In today’s networked society, various sources of competitive information vie for attention and strive to enhance their social influence. Agents with valuable information aim to select a strategic set of influential individuals for information dissemination. This study delves into the Competitive Influence Maximization problem based on the independent cascade model, where an agent selects a seed set to maximize their social influence while contending with uncertain sources of competition. When adopting information, individuals exhibit a bandwagon effect. We begin by demonstrating that the objective function in our problem is neither supermodular nor submodular. Subsequently, we introduce upper and lower bound problems using the Sandwich approach, showcasing their objective functions as submodular and monotone non-decreasing. We propose a greedy algorithm to solve these bounds effectively. A theoretical analysis of the Sandwich approach’s performance is presented, followed by experimental evaluations to assess its effectiveness.

Keywords: Social networks; competitive influence maximization; bandwagon effect; submodular functions; sandwich approach (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1142/S0217595923500343

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