IntelliAd Understanding In-APP Ad Costs From Users Perspective
Cuiyun Gao, Hui Xu, Yichuan Man, Yangfan Zhou, Michael R. Lyu

TL;DR
This paper investigates user-perceived costs of in-app ads by analyzing app reviews and measuring various ad-related costs across different schemes, providing insights for developers to optimize ad integration without harming user experience.
Contribution
It introduces a framework called IntelliAd to automatically measure ad costs from user reviews and compares different ad schemes to understand their impact on users.
Findings
Memory/CPU overhead and battery consumption are major user concerns.
Traffic usage varies across schemes but is less concerning to users.
Different ad schemes have distinct cost profiles affecting user perception.
Abstract
Ads are an important revenue source for mobile app development, especially for free apps, whose expense can be compensated by ad revenue. The ad benefits also carry with costs. For example, too many ads can interfere the user experience, leading to less user retention and reduced earnings ultimately. In the paper, we aim at understanding the ad costs from users perspective. We utilize app reviews, which are widely recognized as expressions of user perceptions, to identify the ad costs concerned by users. Four types of ad costs, i.e., number of ads, memory/CPU overhead, traffic usage, and bettery consumption, have been discovered from user reviews. To verify whether different ad integration schemes generate different ad costs, we first obtain the commonly used ad schemes from 104 popular apps, and then design a framework named IntelliAd to automatically measure the ad costs of each…
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Taxonomy
TopicsGreen IT and Sustainability · Advanced Malware Detection Techniques · Mobile and Web Applications
