Affiliation:
1. Department of Computer Science, University of Texas at Dallas, Richardson, Texas 75080, USA
Abstract
The use of social media has generated huge Online Social Networks (OSN). This network exhibits nice structural properties and has opened door to various research tasks like community detection, link prediction and influence modeling in OSN. There are several models such as linear threshold and independent cascade model proposed in the literature that models the influence diffusion process. Depending on the use-case one may want to amplify or attenuate information in OSN called influence maximization (IM) and rumor blocking (RB), respectively. In terms of marketing, it is called viral marketing. This paper extensively reviews the fundamental research tasks associated with the structure of OSN, groups them into different categories based on the fundamental research area discussed along with its applications. This paper also surveys RB and the various variants of IM found in the literature.
Funder
National Science Foundation
Publisher
World Scientific Pub Co Pte Ltd
Subject
Discrete Mathematics and Combinatorics
Cited by
2 articles.
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