CrowdSurfer: Seamlessly Integrating Crowd-Feedback Tasks into Everyday Internet Surfing

要旨

Crowd feedback overcomes scalability issues of feedback collection on interactive website designs. However, collecting feedback on crowdsourcing platforms decouples the feedback provider from the context of use. This creates more effort for crowdworkers to immerse into such context in crowdsourcing tasks. In this paper, we present CrowdSurfer, a browser extension that seamlessly integrates design feedback collection in crowdworkers' everyday internet surfing. This enables the scalable collection of in situ feedback and, in parallel, allows crowdworkers to flexibly integrate their work into their daily activities. In a field study, we compare the CrowdSurfer against traditional feedback collection. Our qualitative and quantitative results reveal that, while in situ feedback with the CrowdSurfer is not necessarily better, crowdworkers appreciate the effortless, enjoyable, and innovative method to conduct feedback tasks. We contribute with our findings on in situ feedback collection and provide recommendations for the integration of crowdworking tasks in everyday internet surfing.

著者
Saskia Haug
Karlsruhe Insititute of Technology (KIT), Karlsruhe, Germany
Ivo Benke
Karlsruhe Insititute of Technology (KIT), Karlsruhe, Germany
Daniel Fischer
Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Alexander Maedche
Karlsruhe Institute of Technology (KIT), Karlsruhe, DEUTSCHLAND, Germany
論文URL

https://doi.org/10.1145/3544548.3580994

動画

会議: CHI 2023

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)

セッション: Online Communities

Hall B
6 件の発表
2023-04-26 01:35:00
2023-04-26 03:00:00