A Decade of Privacy-Relevant Android App Reviews: Large Scale Trends
CoRR(2024)
摘要
We present an analysis of 12 million instances of privacy-relevant reviews
publicly visible on the Google Play Store that span a 10 year period. By
leveraging state of the art NLP techniques, we can examine what users have been
writing about privacy along multiple dimensions: time, countries, app types,
diverse privacy topics, and even across a spectrum of emotions. We find
consistent growth of privacy-relevant reviews, and explore topics that are
trending (such as Data Deletion and Data Theft), as well as those on the
decline (such as privacy-relevant reviews on sensitive permissions). We find
that although privacy reviews come from more than 200 countries, 33 countries
provide 90
examining the distribution of privacy topics a country's users write about, and
find that geographic proximity is not a reliable indicator that nearby
countries have similar privacy perspectives. We uncover some countries with
unique patterns and explore those herein. Surprisingly, we uncover that it is
not uncommon for reviews that discuss privacy to be positive (32
express pleasure about privacy features within apps or privacy-focused apps. We
also uncover some unexpected behaviors, such as the use of reviews to deliver
privacy disclaimers to developers. Finally, we demonstrate the value of
analyzing app reviews with our approach as a complement to existing methods for
understanding users' perspectives about privacy.
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