Papers
Describing public participation in scientific research. Syracuse University School of Information Studies.
. (2011). Describing Public Participation in Scientific Research.pdf (144.6 KB) . (2011). system_assemblage.pdf (89.24 KB)
Citizen science system assemblages: Toward greater understanding of technologies to support crowdsourced science. Syracuse University School of Information Studies.
. (2011). system_assemblage.pdf (89.24 KB)Poster: Socially intelligent computing to support citizen science. Syracuse, NY: Syracuse University School of Information Studies.
. (2012). SOCS CS SOCS PI poster small.pdf (5.75 MB) . (2020). Novelty_Motivator_2020.pdf (1.15 MB)
. (2011). designing citizen science games.pdf (1 MB)
Crowdsourcing Science: Organizing Virtual Participation in Knowledge Production. Syracuse, NY: Syracuse University.
. (2010). Occasional Groups in Crowdsourcing Platforms. In School of Information Studies. Syracuse University, Syracuse, NY, USA.
. (2021). Dissertation_MH.pdf (3.92 MB)Characterizing Novelty as a Motivator in Online Citizen Science (Syracuse University). In School of Information Studies. Retrieved de https://surface.syr.edu/etd/1046/
. (2019). Imagine All the People: Citizen Science, Artificial Intelligence, and Computational Research. In A Computing Community Consortium (CCC) Quadrennial Paper. Retrieved de https://cra.org/ccc/wp-content/uploads/sites/2/2021/03/CCC-TransitionPaperImagine-All-the-People.pdf
. (2021). Design for Citizen Science Workshop Report. Syracuse, NY: Syracuse University School of Information Studies.
. (2011). CitizenScienceFinalWorkshopReport.pdf (7.43 MB)The Hermeneutics of Trace Data: Building an Apparatus. In IFIP Working Group 8.2 Working Conference.
. (2016). Crowston_Osterlund_Jackson_Mugar_The_Hermeneutics_of_Trace_Data_IFIP8.2_2016 to distribute.pdf (205.13 KB)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
. (2017). cpa143-leeA.pdf (127.53 KB)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
. (2017). cpa137-crowstonA.pdf (1.26 MB)Encouraging Work in Citizen Science: Experiments in Goal Setting and Anchoring. In ACM Conference on Computer Supported Cooperative Work & Social Computing (CSCW). https://doi.org/10.1145/2818052.2869129
. (2016). CSCW-abstract.pdf (423.64 KB)SoCS: Socially intelligent computing to support citizen science. In Proposal submitted to the NSF SOCS program.
. (2010). NSFmaster.pdf (309.26 KB)Teaching Citizen Scientists to Categorize Glitches using Machine-Learning-Guided Training. Computers In Human Behavior, 105, 106198. https://doi.org/10.1016/j.chb.2019.106198
. (2020). MLGT-preprint.pdf (2.43 MB) . (2015). Surveying the citizen science landscape.pdf (50.22 KB)
Supporting and augmenting human and machine learning in citizen science: Lessons from Gravity Spy. Citizen Science: Theory And Practice.
. (In Press). 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
. (2018). crowston fagnot to distribute.pdf (3.76 MB)Shifting forms of Engagement: Volunteer Learning in Online Citizen Science. Proceedings Of The Acm On Human-Computer Interaction, (CSCW), 36. https://doi.org/10.1145/3392841
. (2020). 3392841.pdf (1.13 MB)Preserving the margins: Supporting creativity and resistance on digital participatory platforms. Proceedings Of The Acm: Human-Computer Interaction, 1(CSCW). https://doi.org/10.1145/3134718
. (2017). pacmhci083-mugarSC.pdf (254.77 KB)Knowledge Tracing to Model Learning in Online Citizen Science Projects. Ieee Transactions On Learning Technologies, 13, 123-134. https://doi.org/10.1109/TLT.2019.2936480
. (2020). transaction paper final figures in text.pdf (1.39 MB)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
. (2024). Gravity Spy: Integrating Advanced LIGO Detector Characterization, Machine Learning, and Citizen Science. Classical And Quantum Gravity, 34, 064003. https://doi.org/10.1088/1361-6382/aa5cea
. (2017).