@inbook{59cabfec66c04001bdd46543c7ff471f,
title = "Crowdsourcing for Information Visualization: Promises and Pitfalls",
abstract = "Crowdsourcing offers great potential to overcome the limitations of controlled lab studies. To guide future designs of crowdsourcing-based studies for visualization, we review visualization research that has attempted to leverage crowdsourcing for empirical evaluations of visualizations. We discuss six core aspects for successful employment of crowdsourcing in empirical studies for visualization – participants, study design, study procedure, data, tasks, and metrics & measures. We then present four case studies, discussing potential mechanisms to overcome common pitfalls. This chapter will help the visualization community understand how to effectively and efficiently take advantage of the exciting potential crowdsourcing has to offer to support empirical visualization research.",
author = "Rita Borgo and Bongshin Lee and Benjamin Bach and Sara Fabrikant and Radu Jianu and Andreas Kerren and Stephen Kobourov and Fintan McGee and Luana Micallef and Landesberger, {Tatiana von} and Katrin Ballweg and Stephan Diehl and Paolo Simonetto and Michelle Zhou",
year = "2017",
language = "English",
isbn = "978-3-319-66434-7",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "96--138",
editor = "Daniel Archambault and Helen Purchase and Tobias Hossfeld",
booktitle = "Evaluation in the Crowd: Crowdsourcing and Human-Centered Experiments",
address = "Germany",
}