Big Data Factories book has been published!

Submitted by crowston on Tue, 2017-12-05 07:39

The book has been published by Springer. The book discusses how to use the increasing flood of data created as a byproduct of online behaviour as a source for research. I have a chapter entitled "".

Looking for PhD students!

Submitted by crowston on Fri, 2017-09-15 11:53

I am interested in finding new PhD students interested in work and technology, especially work and intelligent machines. You can find more information on the program . Please get in touch if you have questions or are thinking about applying.

Coordinating advanced crowd work: Extending citizen science

Crowston, K., Mitchell, E. Michelle, & Østerlund, C.. (2018). Coordinating advanced crowd work: Extending citizen science. In Hawai'i International Conference on System Sciences (51st ed.). https://doi.org/10.24251/HICSS.2018.212

Stages of motivation for contributing user-generated content: A theory and empirical test

Crowston, K., & Fagnot, I.. (2018). Stages of motivation for contributing user-generated content: A theory and empirical test. International Journal Of Human-Computer Studies, 109, 89-101. https://doi.org/10.1016/j.ijhcs.2017.08.005

Researchers turn to “citizen scientists” for help identifying gravitational waves

Submitted by crowston on Wed, 2017-01-11 14:22

University of Alabama has a nice about Gravity Spy.

Other popular press coverage: , Symmetry Magazine.

Recruiting messages matter: Message strategies to attract citizen scientists

Lee, T. Kyoung, Crowston, K., Østerlund, C., & Miller, G.. (2017). Recruiting messages matter: Message strategies to attract citizen scientists. In ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW 2017). https://doi.org/10.1145/3022198.3026335

Gravity Spy: Humans, machines and the future of citizen science

Crowston, K., & The Gravity Spy Team. (2017). Gravity Spy: Humans, machines and the future of citizen science. In ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW 2017). https://doi.org/10.1145/3022198.3026329

Levels of trace data for social and behavioural science research

Crowston, K. (2017). Levels of trace data for social and behavioural science research. In S. Matei, Goggins, S., & Jullien, N. (Eds.), Big Data Factories: Collaborative Approaches. https://doi.org/10.1007/978-3-319-59186-5_4

Gamers, citizen scientists, and data: Exploring participant contributions in two games with a purpose

Prestopnik, N., Crowston, K., & Wang, J.. (2017). Gamers, citizen scientists, and data: Exploring participant contributions in two games with a purpose. Computers In Human Behavior, 68, 254–268. https://doi.org/10.1016/j.chb.2016.11.035

National Consortium for Data Science webinar: Humans, Machines, and the Future of Citizen Science:

Submitted by crowston on Sat, 2016-11-05 16:38

I recently gave a webinar for the National Consortium for Data Science on Humans, Machines, and the Future of Citizen Science.

Pages