TY - GEN
T1 - Understanding Incentivized Mobile App Installs on Google Play Store
AU - Farooqi, Shehroze
AU - Feal, Álvaro
AU - Lauinger, Tobias
AU - McCoy, Damon
AU - Shafiq, Zubair
AU - Vallina-Rodriguez, Narseo
N1 - Funding Information:
We would like to thank our shepherd, Maria Papadopouli, and the anonymous reviewers for their useful feedback on this paper. We would also like to thank Sojhal Ismail, Abubakar Aziz, and Muzammil Hussain for their help with data collection. This work is supported in part by the National Science Foundation (under grant numbers 1564329, 1715152, 1814816, and 1954224), the European Union’s Horizon 2020 Innovation Action program (grant agreement number 786741, SMOOTH Project), the Spanish Ministry of Science and Innovation (grant agreement number PID2019-111429RB-C22, ODIO project), and by unrestricted gifts from Facebook and Google.
Publisher Copyright:
© 2020 ACM.
PY - 2020/10/27
Y1 - 2020/10/27
N2 - "Incentivized"advertising platforms allow mobile app developers to acquire new users by directly paying users to install and engage with mobile apps (e.g., create an account, make in-app purchases). Incentivized installs are banned by the Apple App Store and discouraged by the Google Play Store because they can manipulate app store metrics (e.g., install counts, appearance in top charts). Yet, many organizations still offer incentivized install services for Android apps. In this paper, we present the first study to understand the ecosystem of incentivized mobile app install campaigns in Android and its broader ramifications through a series of measurements. We identify incentivized install campaigns that require users to install an app and perform in-app tasks targeting manipulation of a wide variety of user engagement metrics (e.g., daily active users, user session lengths) and revenue. Our results suggest that these artificially inflated metrics can be effective in improving app store metrics as well as helping mobile app developers to attract funding from venture capitalists. Our study also indicates lax enforcement of the Google Play Store's existing policies to prevent these behaviors. It further motivates the need for stricter policing of incentivized install campaigns. Our proposed measurements can also be leveraged by the Google Play Store to identify potential policy violations.
AB - "Incentivized"advertising platforms allow mobile app developers to acquire new users by directly paying users to install and engage with mobile apps (e.g., create an account, make in-app purchases). Incentivized installs are banned by the Apple App Store and discouraged by the Google Play Store because they can manipulate app store metrics (e.g., install counts, appearance in top charts). Yet, many organizations still offer incentivized install services for Android apps. In this paper, we present the first study to understand the ecosystem of incentivized mobile app install campaigns in Android and its broader ramifications through a series of measurements. We identify incentivized install campaigns that require users to install an app and perform in-app tasks targeting manipulation of a wide variety of user engagement metrics (e.g., daily active users, user session lengths) and revenue. Our results suggest that these artificially inflated metrics can be effective in improving app store metrics as well as helping mobile app developers to attract funding from venture capitalists. Our study also indicates lax enforcement of the Google Play Store's existing policies to prevent these behaviors. It further motivates the need for stricter policing of incentivized install campaigns. Our proposed measurements can also be leveraged by the Google Play Store to identify potential policy violations.
KW - Incentivized Installs
KW - Mobile apps
KW - Reputation Manipulation
KW - Spam Installs
UR - http://www.scopus.com/inward/record.url?scp=85097264419&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85097264419&partnerID=8YFLogxK
U2 - 10.1145/3419394.3423662
DO - 10.1145/3419394.3423662
M3 - Conference contribution
AN - SCOPUS:85097264419
T3 - Proceedings of the ACM SIGCOMM Internet Measurement Conference, IMC
SP - 696
EP - 709
BT - IMC 2020 - Proceedings of the 2020 ACM Internet Measurement Conference
PB - Association for Computing Machinery
T2 - 20th ACM Internet Measurement Conference, IMC 2020
Y2 - 27 October 2020 through 29 October 2020
ER -