Papers

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2024
Crowston, K., Erickson, I., & Nickerson, J.. (2024). Editorial: Sharing work with AI: introduction to the special issue on the futures of work in the age of intelligent machines. Information Technology & People, 37(7), 2353 - 2356. https://doi.org/10.1108/ITP-12-2024-994
Bullard, J., Crowston, K., Jackson, C. B., Smith, A. O., & Østerlund, C.. (2024). Folksonomies in crowdsourcing platforms: Three tensions associated with the development of shared language in distributed groups. In The European Conference on Computer-Supported Cooperative Work (ECSCW). https://doi.org/10.48340/ecscw2024_n06
PDF icon ECSCW2024_Folksonomy_Crowdsourcing__Final_.pdf (1.59 MB)
Østerlund, C., Crowston, K., Jackson, C. B., Takou-Ayaoh, M., Wu, Y., & Katsaggelos, A. K.. (2024). Mutual learning in human-AI interaction. In Trust and Reliance in Evolving Human-AI Workflows (TREW) Workshop, ACM CHI Conference. Presented at the Trust and Reliance in Evolving Human-AI Workflows (TREW) Workshop, ACM CHI Conference, Honolulu, HI.
PDF icon TREW_Workshop_Paper_2024.pdf (392.26 KB)
2023
Petridis, S., Diakopoulos, N., Crowston, K., Hansen, M., Henderson, K., Jastrzebski, S., et al.. (2023). AngleKindling: Supporting Journalistic Angle Ideation with Large Language Models. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3544548.3580907
Borycz, J., Olendorf, R., Specht, A., Grant, B., Crowston, K., Tenopir, C., et al.. (2023). Perceived benefits of open data are improving but scientists still lack resources, skills, and rewards. Humanities And Social Sciences Communications, 10(1). https://doi.org/10.1057/s41599-023-01831-7
2020
Choudhury, P., Crowston, K., Dahlander, L., Minervini, M. S., & Raghuram, S.. (2020). GitLab: Work where you want, when you want. Journal Of Organizational Design, 9(1), 23. https://doi.org/10.1186/s41469-020-00087-8
PDF icon s41469-020-00087-8.pdf (1.14 MB)
2017
Crowston, K., & Squire, M.. (2017). Lessons Learned from a Decade of FLOSS Data Collection. In S. Adam Matei, Jullien, N., & Goggins, S. P. (Eds.), Big Data Factories (pp. 79 - 100). https://doi.org/10.1007/978-3-319-59186-5