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Papers

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2024
PDF icon GAI_and_skills.pdf (281.94 KB)
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)
Öcal, A., & Crowston, K.. (2024). Framing and feelings on social media: The futures of work and intelligent machines. Information, Technology & People. https://doi.org/10.1108/ITP-01-2023-0049
PDF icon frames to share.pdf (391.17 KB)
Zevin, M., Jackson, C. B., Doctor, Z., Wu, Y., Østerlund, C., L. Johnson, C., et al.. (2024). Gravity Spy: Lessons Learned and a Path Forward. European Physical Journal Plus, 139, Article 100. https://doi.org/10.1140/epjp/s13360-023-04795-4
PDF icon Implications for hybrid newswork from the activities of local US television journalists during COVID to share.pdf (323.75 KB)
Dolata, M., & Crowston, K.. (2024). Making sense of AI systems development. Ieee Transactions On Software Engineering, 50(1), 123–140. https://doi.org/10.1109/TSE.2023.3338857
PDF icon sensemaking_tse_to_share.pdf (619.73 KB)
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)
Wang, S., Menon, S., Long, T., Henderson, K., Li, D., Crowston, K., et al.. (2024). ReelFramer: Human-AI Co-Creation for News-to-Video Translation. In CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3613904.3642868
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
Crowston, K., Jackson, C. B., Corieri, I., & Østerlund, C.. (2023). Design principles for background knowledge to enhance learning in citizen science. In Information for a Better World: Normality, Virtuality, Physicality, Inclusivity: 18th International Conference, iConference (pp. 563–580). https://doi.org/10.1007/978-3-031-28032-0_43
PDF icon Design_Background_iConf.pdf (3.78 MB)
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
2022
Ågerfalk, P. J., Conboy, K., Crowston, K., Jarvenpaa, S. L., Lundström, J. Eriksson, Mikalef, P., & Ram, S.. (2022). Artificial intelligence in information systems: State of the art and research roadmap. Communications Of The Association For Information Systems (Cais), 50. https://doi.org/10.17705/1CAIS.05017
PDF icon Artificial Intelligence in Information Systems State of the Art.pdf (1 MB)
Henderson, K., Raheja, R., & Crowston, K.. (2022). Communicating with the masses from isolation: What happened when local television journalists worked from home. In Hawai'i International Conference on System Sciences. Presented at the Hawai'i International Conference on System Sciences, Virtual due to COVID. https://doi.org/10.24251/HICSS.2022.858
PDF icon Journalists work from home_HICSS Version_Final Submission_Unlinked.pdf (221.34 KB)
Specht, A., & Crowston, K.. (2022). Interdisciplinary collaboration from diverse science teams can produce significant outcomes. Plos One, 17(11). https://doi.org/10.1371/journal.pone.0278043
PDF icon Interdisciplinary collaboration from diverse science teams can produce significant outcomes.pdf (904.84 KB)
Dolata, M., Crowston, K., & Schwabe, G.. (2022). Project archetypes: A blessing and a curse for AI development. In International Conference on Information Systems (ICIS). Presented at the International Conference on Information Systems (ICIS), Copenhagen, Denmark. Retrieved de https://aisel.aisnet.org/icis2022/is_design/is_design/6
PDF icon icis_archetypes_rev1_v20_zora.pdf (433.37 KB)

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