Year: 2013
Type: article
Abstract: Online social networks play a major role in the spread of information at very large scale. A lot of effort have been made in order to understand this phenomenon, ranging from popular topic detection to information diffusion modeling, including influential spreaders identification. In this article, we present a survey of representative methods dealing with these issues and propose a taxonomy that summarizes the state-of-the-art. The objective is to provide a comprehensive analysis and guide of existing efforts around information diffusion in social networks. This survey is intended to help researchers in quickly understanding existing works and possible improvements to bring.
Source: ACM SIGMOD Record
Authors: Adrien Guille, Hakim Hacid, Cecile Favre, Djamel A. Zighed
Institutions: Université Lumière Lyon 2, Alcatel-Lucent (France)
Language: English
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2054476043