A Novel Information Diffusion Model Based on Psychosocial Factors with Automatic Parameter Learning

Sabina-Adriana Floria1 and Florin Leon1

  1. Faculty of Automatic Control and Computer Engineering, “Gheorghe Asachi” Technical University of Iași
    Bd. D. Mangeron 27, 700050, Iași, Romania
    {sabina.floria, florin.leon}@tuiasi.ro


Online social networks are the main choice of people to maintain their social relationships and share information or opinions. Estimating the actions of a user is not trivial because an individual can act spontaneously or be influenced by external factors. In this paper we propose a novel model for imitating the evolution of the information diffusion in a network as well as possible. Each individual is modeled as a node with two factors (psychological and sociological) that control its probabilistic transmission of information. The psychological factor refers to the node’s preference for the topic discussed, i.e. the information diffused. The sociological factor takes into account the influence of the neighbors’ activity on the node, i.e. the gregarious behavior. A genetic algorithm is used to automatically tune the parameters of the model in order to fit the evolution of information diffusion observed in two real-world datasets with three topics. The reproduced diffusions show that the proposed model imitates the real diffusions very well.

Key words

social networks, information diffusion, psychological factors, sociological factors, genetic algorithm

Digital Object Identifier (DOI)


Publication information

Volume 18, Issue 3 (June 2021)
Year of Publication: 2021
ISSN: 1820-0214 (Print) 2406-1018 (Online)
Publisher: ComSIS Consortium

Full text

DownloadAvailable in PDF
Portable Document Format

How to cite

Floria, S., Leon, F.: A Novel Information Diffusion Model Based on Psychosocial Factors with Automatic Parameter Learning. Computer Science and Information Systems, Vol. 18, No. 3, 703–728. (2021), https://doi.org/10.2298/CSIS200415050F