A novel information diffusion model based on psychosocial factors with automatic parameter learning

Computer Science and Information Systems

article

Sabina-Adriana Floria¹  Florin Leon¹ 

[1] Faculty of Automatic Control and Computer Engineering, “Gheorghe Asachi” TechnicalUniversity of Iași

关键词: social networks;    information diffusion;    psychological factors;    sociological factors;    genetic algorithm;   

DOI  :  10.2298/CSIS200415050F

学科分类：土木及结构工程学

来源: Computer Science and Information Systems

【 摘 要 】

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. Agenetic 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.

【 授权许可】

CC BY-NC-ND