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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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    1. Lei Ji & Jian-Guo Liu & Lei Hou & Qiang Guo, 2015. "Identifying the Role of Common Interests in Online User Trust Formation," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-15, July.
    2. Zan Huang & Daniel D. Zeng & Hsinchun Chen, 2007. "Analyzing Consumer-Product Graphs: Empirical Findings and Applications in Recommender Systems," Management Science, INFORMS, vol. 53(7), pages 1146-1164, July.
    3. Ren, Zhuo-Ming & Shi, Yu-Qiang & Liao, Hao, 2016. "Characterizing popularity dynamics of online videos," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 453(C), pages 236-241.
    4. Ni, Jing & Zhang, Yi-Lu & Hu, Zhao-Long & Song, Wen-Jun & Hou, Lei & Guo, Qiang & Liu, Jian-Guo, 2014. "Ceiling effect of online user interests for the movies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 134-140.
    5. Wang, Jia-Hua & Guo, Qiang & Yang, Kai & Zhang, Yi-Lu & Han, Jingti & Liu, Jian-Guo, 2016. "Popularity and user diversity of online objects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 480-486.
    6. Liu, Xiao-Lu & Guo, Qiang & Hou, Lei & Cheng, Can & Liu, Jian-Guo, 2015. "Ranking online quality and reputation via the user activity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 629-636.
    7. Jianguo Liu & Lei Hou & Yi-Lu Zhang & Wen-Jun Song & Xue Pan, 2013. "Empirical Analysis Of The Clustering Coefficient In The User-Object Bipartite Networks," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 24(08), pages 1-10.
    8. Li-Ying Tang & Sheng-Nan Li & Jian-Hong Lin & Qiang Guo & Jian-Guo Liu, 2016. "Community structure detection based on the neighbor node degree information," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 27(04), pages 1-11, April.
    9. Robert M. Bond & Christopher J. Fariss & Jason J. Jones & Adam D. I. Kramer & Cameron Marlow & Jaime E. Settle & James H. Fowler, 2012. "A 61-million-person experiment in social influence and political mobilization," Nature, Nature, vol. 489(7415), pages 295-298, September.
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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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