|In 1998 less than 10 percent of the global population held cell phone subscriptions. By the end of 2011 this number had increased to 87 percent, accounting for over 5.9 billion subscribers worldwide. Due to this high rate of adoption cell phones have become one of the most pervasive pieces of technology in society, changing the way we think about communication and influencing our daily lives. Society as a whole currently stands on the precipice of mass adoption of the next generation of cellular communication, the smart phone. These devices hold just as much, if not more, ability to change the way we think about interpersonal communication.
149 million smart phones were sold in the fourth quarter of 2011 with close to half of these devices running the Android operating system. Smart phones grant end users the ability to install third-party software on their devices customizing the functional of a device to their specific needs. These third-party programs, or apps, are generally hosted on markets which allow a user to easily browse, purchase, and download apps of their choosing. While Google hosts an official Android market known as Google Play many third-party markets have been established as well. Android users have heavily utilized these markets, installing an average of 35 apps on each device owned and downloading more than 10 billion apps from Google’s official market alone.
Yet for all the popularity of the Android operating system and the app markets which accompany it very little demographic information can be found on these markets as a whole. In this work we present a process for acquiring a large body of Android apps, reverse engineering them, and then extracting demographic information from this data. We then compile a demographic overview of four different third-party markets examining attributes of these markets such as app permissions and SDKs used, localization utilization, the employment of monetization schemes, and many others. Finally, we compare the results across all four markets looking for trends in that emerge in our data set.