Source code associated to the paper "Social diffusion modeling of the dynamics of premium content adoption in freemium apps", submitted to JMR
The freemium business model is being increasingly used in software services and mobile apps but they do not work if users do not adopt the premium services. We investigate the social influence role within premium conversions and evaluate rewarding and targeting strategies to expand premium users. For this investigation we propose a general agent-based modeling framework that aggregates social network-level users interactions. We adapt the model to a real hedonic online app, Animal Jam, by building a decision support system with two adoption levels: one to forecast the most likely users to become premium in the near future and a second one to forecast the aggregate number of app premiums over time. Our results indicate that we can forecast both premium adoption levels and that premium adoption has a social dynamics based on complex contagion. We also show that it is possible to increase the number of premiums by performing rewarding policies and efficiently targeting the campaigns to the most likely users to adopt premium services.
What is this repository for?
- Source code in Java with parameter files, JAVADOC, JAR file, and data for replicating the experiments of the paper.
- Version: 1.0