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Uncovering the popularity mechanisms for Facebook applications

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Listed:
  • Li, Sheng-Nan
  • Guo, Qiang
  • Yang, Kai
  • Liu, Jian-Guo
  • Zhang, Yi-Cheng

Abstract

Understanding the popularity dynamics of online application(App) is significant for the online social systems. In this paper, by dividing the Facebook Apps into different groups in terms of their popularities, we empirically investigate the popularity dynamics for different kinds of Facebook Apps. Then, taking into account the influence of cumulative and recent popularities on the user choice, we present a model to regenerate the growth of popularity for different App groups. The experimental results of 917 Facebook Apps show that as the popularities of Facebook Apps increase, the recent popularity plays more important role. Specifically, the recent popularity plays more important role in regenerating the popularity dynamics for more popular Apps, and the cumulative popularity plays more important role for unpopular Apps. We also conduct temporal analysis on the growth characteristic of individual App by comparing the increment at each time with the average of historical records. The results show that the growth of more popular App tends to fluctuate more greatly. Our work may shed some lights for deeply understanding the popularity mechanism for online applications.

Suggested Citation

  • Li, Sheng-Nan & Guo, Qiang & Yang, Kai & Liu, Jian-Guo & Zhang, Yi-Cheng, 2018. "Uncovering the popularity mechanisms for Facebook applications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 422-429.
    • Handle: RePEc:eee:phsmap:v:494:y:2018:i:c:p:422-429
    DOI: 10.1016/j.physa.2017.12.006
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    References listed on IDEAS

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    Cited by:

    1. Yanbo Zhou & Hongbing Cheng & Qu Li & Weihong Wang, 2020. "Diversity of temporal influence in popularity prediction of scientific publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(1), pages 383-392, April.
    2. Liu, Jian-Guo & Yang, Zhen-Hua & Li, Sheng-Nan & Yu, Chang-Rui, 2018. "A generative model for the collective attention of the Chinese stock market investors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1175-1182.

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