Crowdsourced Online Biometric Studies: Is the juice worth the squeeze?

Robert W Hammond, Yuqi Wang
Muma Business Review  •  Volume 7  •  2023  •  pp. 141-148
While promising, online biometric studies with crowdsourced participants have vagaries that can limit success. This paper shares researcher experience with biometric online data collection and a study that compared the differences of online and lab-based eye tracking (ET) and facial expression (FE) data.

Students and the public were separated into two groups to place orders from a well-known restaurant online menu application. Group 1 accessed the menu web application routed through an online biometric data collection tool while Group 2 interacted with the menu web application through a desktop application that collected the biometric data.

The study found little difference in the user experience metrics, the facial expression data, or the number of gaze points between the two data collection methods. Interestingly and consistent with field experience a significant difference in the ET data was observed.

The vagaries of the field present significant hazards for researchers and even more so if study participants are compensated. Recommendations for researchers to optimize research effort are provided regarding recruitment, participant compensation, analysis effort and expertise, maximizing the usable data, and employing eye tracking tools.
Affective Computing, Emotional AI, Biometrics, Online Data Collection, Crowdsourcing, Eye Tracking, Facial Expression Analysis
26 total downloads
Share this
 Back

Back to Top ↑