TY - GEN
T1 - A Deep Dive into the Featured iOS Apps
AU - Wang, Liu
AU - Wang, Haoyu
AU - Wang, Huiyi
AU - Li, Li
AU - Wang, Yi
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/8/4
Y1 - 2023/8/4
N2 - Millions of apps in markets have made it difficult for mobile users to find fancy and high quality apps. Mobile app markets have deployed mechanisms to recommend apps to users. Apple usually features apps in the iOS App Store, and mobile users could see the featured apps as soon as they open the App Store. In general, getting apps featured is an achievement all developers strive towards and it is a common belief that getting app featured means that the app is becoming popular. However, the official app recommendation mechanism has not been characterized yet. To fill the void, we present a large-scale and longitudinal study of featured apps on iOS App Store. Specifically, we collaborate with our industry partner to monitor the iOS App Store and collect the daily featured apps in both the US and China, covering a span of over 1.5 years. Based on this comprehensive dataset, we characterize the featured apps from various dimensions and investigate the impact of app recommendation on app popularity. We have revealed a number of observations that are unknown to the community. Most importantly, we observe that although getting featured indeed has a positive effect for most apps, the duration of this effect is short-lived. In addition, there are times when the recommendations are ineffective, and we propose some potential reasons and tips for this. Our study can offer practical implications on app promotion to stakeholders in the mobile app ecosystem.
AB - Millions of apps in markets have made it difficult for mobile users to find fancy and high quality apps. Mobile app markets have deployed mechanisms to recommend apps to users. Apple usually features apps in the iOS App Store, and mobile users could see the featured apps as soon as they open the App Store. In general, getting apps featured is an achievement all developers strive towards and it is a common belief that getting app featured means that the app is becoming popular. However, the official app recommendation mechanism has not been characterized yet. To fill the void, we present a large-scale and longitudinal study of featured apps on iOS App Store. Specifically, we collaborate with our industry partner to monitor the iOS App Store and collect the daily featured apps in both the US and China, covering a span of over 1.5 years. Based on this comprehensive dataset, we characterize the featured apps from various dimensions and investigate the impact of app recommendation on app popularity. We have revealed a number of observations that are unknown to the community. Most importantly, we observe that although getting featured indeed has a positive effect for most apps, the duration of this effect is short-lived. In addition, there are times when the recommendations are ineffective, and we propose some potential reasons and tips for this. Our study can offer practical implications on app promotion to stakeholders in the mobile app ecosystem.
KW - app mining
KW - app store
KW - featured apps
KW - iOS
UR - https://www.scopus.com/pages/publications/85175733567
U2 - 10.1145/3609437.3609467
DO - 10.1145/3609437.3609467
M3 - 会议稿件
AN - SCOPUS:85175733567
T3 - ACM International Conference Proceeding Series
SP - 112
EP - 122
BT - 14th Asia-Pacific Symposium on Internetware, Internetware 2023 - Proceedings
PB - Association for Computing Machinery
T2 - 14th Asia-Pacific Symposium on Internetware, Internetware 2023
Y2 - 4 August 2023 through 6 August 2023
ER -