Unveiling the adoption and cascading process of OSN-based gifting applications

This paper demystifies the adoption and cascading process of OSN-based applications that grow via user invitations. We analyze a detailed large-scale dataset of a popular Facebook gifting application, iHeart, that contains more than 2 billion entries of user activities generated by 190 million users during a span of 64 weeks. We investigate: (1) how users invite their friends to an OSN-based application, (2) what factors drive the cascading process of application adoptions, and (3) what are the good predictors of the ultimate cascade sizes. We find that sending or receiving a large number of invitations does not necessarily help to recruit new users to iHeart. We also identify a set of distinctive features that are good predictors of the growth of the application adoptions in terms of final population size. Finally, based on the insights learned from our analyses, we propose a prediction model to infer whether a cascade of application adoption will continue to grow in the future based on observing the initial adoption process. Results show our proposed model can achieve high precision (over 80%) in iHeart as well as in another OSN-based gifting application, Hugged.