Preferential information dynamics model for online social networks

Minglei Fu, Hongbo Yang, Jun Feng, Wen Guo, Zichun Le, Dmytro Lande and Dmytro Manko

Physica A: Statistical Mechanics and its Applications, 2018, vol. 506, issue C, 993-1005

Abstract: In recent years, online social networks have become an important site for companies to promote their latest products. Consequently, evaluating how many clients are affected by preferential information distributed in online social networks has become essential. In this paper, a novel dynamic model called the follower super forwarder client (FSFC) model is proposed to address the spreading behavior of preferential information in online social networks. The mean field theory is adopted to describe the formulas of the FSFC model and the key parameters of the model are derived from the past forwarding data of the preferential information. The edge between a large-degree node to a small-degree node has a greater weight. In addition, two kinds of infection probabilities are adopted for large-degree node forwarders and small-degree node forwarders. To evaluate the performance of the FSFC model, preferential data published on the Sina microblog (www.weibo.com) for the Vivo smartphone, Alibaba’s Tmall shopping site, and the Xiaomi phone were selected as real cases. Simulation results indicate that the relative errors of the output of the FSFC model compared with the actual data are 0.0068% (Vivo smartphone), 0.0085% (Tmall), and 0.032% (Xiaomi phone), respectively. The results verify that the FSFC model is a feasible model for describing the spreading behavior of preferential information in online social networks.

Keywords: Dynamic model; Scale-free network; Preferential information spread model (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437118305533
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:506:y:2018:i:c:p:993-1005

DOI: 10.1016/j.physa.2018.05.017

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().