Identifying Multiple Influential Users Based on the Overlapping Influence in Multiplex Networks

Abstract

Online social networks (OSNs) are interaction platforms that can promote knowledge spreading, rumor propagation, and virus diffusion. Identifying influential users in OSNs is of great significance for accelerating the information propagation especially when information is able to travel across multiple channels. However, most previous studies are limited to a single network or select multiple influential users based on the centrality ranking result of each user, not addressing the overlapping influence (OI) among users. In practice, the collective influence of multiple users is not equal to the total sum of these users' influences. In this paper, we propose a novel OI-based method for identifying multiple influential users in multiplex social networks. We first define the effective spreading shortest path (ESSP) by utilizing the concept of spreading rate in order to denote the relative location of users. Then, the collective influence is quantified by taking the topological factor and the location distribution of users into account. The identified users based on our proposed method are central and relatively scattered with a low overlapping influence. With the Susceptible-Infected-Recovered (SIR) model, we estimate our proposed method with other benchmark algorithms. Experimental results in both synthetic and real-world networks verify that our proposed method has a better performance in terms of the spreading efficiency.INDEX TERMS Multiplex networks, influential users, overlapping influence, shortest path.

Association Rule Analysis-Based Identification of Influential Users in爐he燬ocial Media

“…In all the other areas the user role is one of the most important factors, the user role includes finding the influence of users on social media and bloggers, in other areas of related work the ability to find influential users might also affect [10]. As finding social media users' influence is important, likewise it is also important to identify the potential bloggers.…”

“…A large number of companies are moving their focus on influential users. Based on existing studies, finding influential users is dependent upon the location of users in the blogging network [10] social web activities like others and actions of users circulate to large audience so this is so interesting to find influential bloggers is an active research field in various domain [11]. To search out the influential users has a big relevance to online shopping and advertisements so identifying influential users using sentiment features has also been done [12].…”