An Empirical Study of In-App Advertising Issues Based on Large Scale App
Review Analysis
- URL: http://arxiv.org/abs/2008.12112v1
- Date: Sat, 22 Aug 2020 05:38:24 GMT
- Title: An Empirical Study of In-App Advertising Issues Based on Large Scale App
Review Analysis
- Authors: Cuiyun Gao, Jichuan Zeng, David Lo, Xin Xia, Irwin King, Michael R.
Lyu
- Abstract summary: We present a large-scale analysis on ad-related user feedback from App Store and Google Play.
From a statistical analysis of 36,309 ad-related reviews, we find that users care most about the number of unique ads and ad display frequency during usage.
Some ad issue types are addressed more quickly by developers than other ad issues.
- Score: 67.58267006314415
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: In-app advertising closely relates to app revenue. Reckless ad integration
could adversely impact app reliability and user experience, leading to loss of
income. It is very challenging to balance the ad revenue and user experience
for app developers.
In this paper, we present a large-scale analysis on ad-related user feedback.
The large user feedback data from App Store and Google Play allow us to
summarize ad-related app issues comprehensively and thus provide practical ad
integration strategies for developers. We first define common ad issues by
manually labeling a statistically representative sample of ad-related feedback,
and then build an automatic classifier to categorize ad-related feedback. We
study the relations between different ad issues and user ratings to identify
the ad issues poorly scored by users. We also explore the fix durations of ad
issues across platforms for extracting insights into prioritizing ad issues for
ad maintenance.
We summarize 15 types of ad issues by manually annotating 903/36,309
ad-related user reviews. From a statistical analysis of 36,309 ad-related
reviews, we find that users care most about the number of unique ads and ad
display frequency during usage. Besides, users tend to give relatively lower
ratings when they report the security and notification related issues.
Regarding different platforms, we observe that the distributions of ad issues
are significantly different between App Store and Google Play. Moreover, some
ad issue types are addressed more quickly by developers than other ad issues.
We believe the findings we discovered can benefit app developers towards
balancing ad revenue and user experience while ensuring app reliability.
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