Predicting the future trend of popularity by network diffusion

An ZENG, Chi Ho YEUNG

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Conventional approaches to predict the future popularity of products are mainly based on extrapolation of their current popularity, which overlooks the hidden microscopic information under the macroscopic trend. Here, we study diffusion processes on consumer-product and citation networks to exploit the hidden microscopic information and connect consumers to their potential purchase, publications to their potential citers to obtain a prediction for future item popularity. By using the data obtained from the largest online retailers including Netflix and Amazon as well as the American Physical Society citation networks, we found that our method outperforms the accurate short-term extrapolation and identifies the potentially popular items long before they become prominent. Copyright © 2016 Author(s).
Original languageEnglish
Article number063102
JournalChaos: An Interdisciplinary Journal of Nonlinear Science
Volume26
Issue number6
DOIs
Publication statusPublished - Jun 2016

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Extrapolation
Consumer products

Citation

Zeng, A., & Yeung, C. H. (2016, June). Predicting the future trend of popularity by network diffusion. Chaos: An Interdisciplinary Journal of Nonlinear Science, 26(6). Retrieved June 28, 2016, from http://dx.doi.org/10.1063/1.495301