iPhone's Digital Marketplace: Characterizing the Big Spenders. Kooti, F., Grbovic, M., Aiello, L. M., Bax, E., & Lerman, K. In Proceedings of the 10th International ACM Conference on Web Search and Data Mining, 2017. ACM.
abstract   bibtex   
With mobile shopping surging in popularity, people are spending ever more money on digital purchases through their mobile devices and phones. However, few large-scale studies of mobile shopping exist. In this paper we analyze a large data set consisting of more than 776M digital purchases made on Apple mobile devices that include songs, apps, and in-app purchases. We find that 61% of all the spending is on in-app purchases and that the top 1% of users are responsible for 59% of all the spending. These big spenders are more likely to be male and older, and less likely to be from the US. We study how they adopt and abandon individual app, and find that, after an initial phase of increased daily spending, users gradually lose interest: the delay between their purchases increases and the spending decreases with a sharp drop toward the end. Finally, we model the in-app purchasing behavior in multiple steps: 1) we model the time between purchases; 2) we train a classifier to predict whether the user will make a purchase from a new app or continue purchasing from the existing app; and 3) based on the outcome of the previous step, we attempt to predict the exact app, new or existing, from which the next purchase will come. The results yield
@INPROCEEDINGS{Kooti2017wsdm,
  author =       {Farshad Kooti and Mihajlo Grbovic and Luca Maria Aiello and Eric Bax and Kristina Lerman},
  title =        {iPhone's Digital Marketplace: Characterizing the Big Spenders},
  booktitle =    {Proceedings of the 10th International ACM Conference on Web Search and Data Mining},
  year =         {2017},
  pages =        {},
  publisher =    {ACM},
  abstract =     {With mobile shopping surging in popularity, people are spending ever more money on digital purchases through their mobile devices and phones. However, few large-scale studies of mobile shopping exist. In this paper we analyze a large data set consisting of more than 776M digital purchases made on Apple mobile devices that include songs, apps, and in-app purchases. We find that 61\% of all the spending is on in-app purchases and that the top 1\% of users are responsible for 59\% of all the spending. These big spenders are more likely to be male and older, and less likely to be from the US. We study how they adopt and abandon individual app, and find that, after an initial phase of increased daily spending, users gradually lose interest: the delay between their purchases increases and the spending decreases with a sharp drop toward the end. Finally, we model the in-app purchasing behavior in multiple steps: 1) we model the time between purchases; 2) we train a classifier to predict whether the user will make a purchase from a new app or continue purchasing from the existing app; and 3) based on the outcome of the previous step, we attempt to predict the exact app, new or existing, from which the next purchase will come. The results yield},
  keywords =     {social-dynamics},
}
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