@article{Qiu2018, 
author = {Benliu Qiu and Ningxuan Zhang},
title = {A review on graphical evolutionary game for information diffusion on social networks},
year = {2018},
journal = {International Journal of Crowd Science},
volume = {2},
number = {3},
pages = {259-271},
keywords = {Crowd-sourced design and engineering, Information diffusion, Crowdsourced Big Data and analytics, Evolutionary game, Models and methods for Crowd Science and Engineering},
url = {https://www.sciopen.com/article/10.1108/IJCS-06-2018-0011},
doi = {10.1108/IJCS-06-2018-0011},
abstract = {PurposeWith the recent development of science and technology, research on information diffusion has become increasingly important.Design/methodology/approachTo analyze the process of information diffusion, researchers have proposed a framework with graphical evolutionary game theory (EGT) according to the theory of biological evolution.FindingsThrough this method, one can study and even predict information diffusion.Originality/valueThis paper summarizes three existing works using graphical EGT to discuss how to obtain the static state and the dynamics of information diffusion in social network.}
}