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Title: The TikTok Tradeoff: Compelling Algorithmic Content at the Expense of Personal Privacy
This paper presents the results of an interview study with twelve TikTok users to explore user awareness, perception, and experiences with the app’s algorithm in the context of privacy. The social media entertainment app TikTok collects user data to cater individualized video feeds based on users’ engagement with presented content which is regulated in a complex and overly long privacy policy. Our results demonstrate that participants generally have very little knowledge of the actual privacy regulations which is argued for with the benefit of receiving free entertaining content. However, participants experienced privacy-related downsides when algorithmically catered video content increasingly adapted to their biography, interests, or location and they in turn realized the detail of personal data that TikTok had access to. This illustrates the tradeoff users have to make between allowing TikTok to access their personal data and having favorable video consumption experiences on the app.  more » « less
Award ID(s):
1852260
NSF-PAR ID:
10313202
Author(s) / Creator(s):
;
Date Published:
Journal Name:
20th International Conference on Mobile and Ubiquitous Multimedia (MUM 2021), December 5–8, 2021, Leuven, Belgium. ACM, New York, NY, USA
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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