Analysis of Online Social Network Connections for Identification of Influential Users
Document Type
Article
Publication Date
1-1-2018
Abstract
Online social networks (OSNs) are structures that help users to interact, exchange, and propagate new ideas. The identification of the influential users in OSNs is a significant process for accelerating the propagation of information that includes marketing applications or hindering the dissemination of unwanted contents, such as viruses, negative online behaviors, and rumors. This article presents a detailed survey of influential users’ identification algorithms and their performance evaluation approaches in OSNs. The survey covers recent techniques, applications, and open research issues on analysis of OSN connections for identification of influential users.
Keywords
Big data, Complex networks, Identification algorithms, Influential users, OSNs, Social media
Divisions
fsktm
Funders
University of Malaya Research Grant (subgrant (D) of RP059-17SBS)
Publication Title
ACM Computing Surveys
Volume
51
Issue
1
Publisher
Association for Computing Machinery