Modeling Human Activity with Seasonality Bursty Dynamics

Quansi Wen, Choujun Zhan*, Ying Gao, Xiping Hu, Edith Ngai, Bin Hu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

The public's purchase incentive increases dramatically during the holiday season and subsequently returns to normal levels. This seasonality is common in various scenarios and highlights the following questions: how does the public's purchase incentive fluctuate over the course of a year? Which factors are conducive to this seasonal behavior and how can they be modeled? In this paper, we propose a model that explicitly integrates temporal point process theory with the construction of a networked community, to describe the dynamics of collective action propagation with seasonal fluctuation. Furthermore, a database is constructed of sales records for 21 video game consoles and 13 237 video games in France, Germany, Japan, the U.K., the USA, and worldwide from 1989 to 2018. Experimental results suggest that peak desire always appears in the holiday season about one week before Christmas and is about four times higher than consumption desire in a normal period in all areas.

Original languageEnglish
Article number8755465
Pages (from-to)1130-1139
Number of pages10
JournalIEEE Transactions on Industrial Informatics
Volume16
Issue number2
DOIs
Publication statusPublished - Feb 2020
Externally publishedYes

Keywords

  • Complex network
  • temporal human behavior
  • temporal point processes
  • video game industry

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