Modelling of information diffusion on social networks with applications to WeChat

Liang Liu, Bo Qu, Bin Chen, Alan Hanjalic and Huijuan Wang

Physica A: Statistical Mechanics and its Applications, 2018, vol. 496, issue C, 318-329

Abstract: Traces of user activities recorded in online social networks open new possibilities to systematically understand the information diffusion process on social networks. From the online social network WeChat, we collected a large number of information cascade trees, each of which tells the spreading trajectory of a message/information such as which user creates the information and which users view or forward the information shared by which neighbours. In this work, we propose two heterogeneous non-linear models, one for the topologies of the information cascade trees and the other for the stochastic process of information diffusion on a social network. Both models are validated by the WeChat data in reproducing and explaining key features of cascade trees.

Keywords: Information cascade; Stochastic model; Social networks; WeChat; Random recursive tree (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:496:y:2018:i:c:p:318-329

DOI: 10.1016/j.physa.2017.12.026

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