The Spreading of Information in Online Social Networks through Cellular Automata. (1st November 2018)

• Record Type: Journal Article
• Authors: Wang, Yuda; Li, Gang
• Other Names: Volchenkov Dimitri Academic Editor.
• Is Part Of: Complexity. Volume 2018(2018)
• Publication Date: 2018-11-01
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2018/1890643
• Languages: English
• ISSNs: 1076-2787

Abstract

Abstract : Epidemic dynamics in complex networks have been extensively studied. Due to the similarity between information and disease spreading, most studies on information dynamics use epidemic models and merely consider the characteristics of online social networks and individual's cognitive. In this paper, we propose an online social networks information spreading (OSIS) model combining epidemic models and individual's cognitive psychology. Then we design a cellular automata (CA) method to provide a computational method for OSIS. Finally, we use OSIS and CA to simulate the spreading and evolution of information in online social networks. The experimental results indicate that OSIS is effective. Firstly, individual's cognition affects online information spreading. When infection rate is low, it prevents the spreading, whereas when infection rate is sufficiently high, it promotes transmission. Secondly, the explosion of online social network scale and the convenience of we-media greatly increase the ability of information dissemination. Lastly, the demise of information is affected by both time and heat decay rather than probability. We believe that these findings are in the right direction for perceiving information spreading in online social networks and useful for public management policymakers seeking to design efficient programs.