WildKey: A Privacy-Aware Keyboard Toolkit for Data Collection In-The-Wild
Andr\'e Rodrigues, Andr\'e Santos, Kyle Montague, Hugo Nicolau and, Tiago Guerreiro

TL;DR
WildKey is an Android keyboard toolkit designed for privacy-aware in-the-wild data collection of touch and text-entry behaviors, enabling realistic user studies outside laboratory settings.
Contribution
The paper introduces WildKey, a novel Android keyboard toolkit that facilitates privacy-preserving in-the-wild data collection for behavioral analysis.
Findings
Supports implicit and explicit data collection
Ensures user privacy and compliance
Enables realistic in-the-wild user studies
Abstract
Touch data, and in particular text-entry data, has been mostly collected in the laboratory, under controlled conditions. While touch and text-entry data have consistently shown its potential for monitoring and detecting a variety of conditions and impairments, its deployment in-the-wild remains a challenge. In this paper, we present WildKey, an Android keyboard toolkit that allows for the usable deployment of in-the-wild user studies. WildKey is able to analyze text-entry behaviors through implicit and explicit text-entry data collection while ensuring user privacy. We detail each of the WildKey's components and features, all of the metrics collected, and discuss the steps taken to ensure user privacy and promote compliance.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
