Papers
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Which Way Did They Go? Newcomer Movement through the Zooniverse. In 19th ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW). https://doi.org/10.1145/2818048.2835197
. (2016). 
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). 
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). 
. (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, 9(1), 42. https://doi.org/10.5334/cstp.738
. (2024). 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). 
SoCS: Socially intelligent computing to support citizen science. In Proposal submitted to the NSF SOCS program.
. (2010). 
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). 
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). 
Purposeful gaming & socio-computational systems: A citizen science design case. In Group '12 Conference. Presented at the Group '12 Conference, Sanibel Island, FL, USA.
. (2012). 
Poster: Socially intelligent computing to support citizen science. Syracuse, NY: Syracuse University School of Information Studies.
. (2012). 
Planet Hunters and Seafloor Explorers: Legitimate Peripheral Participation Through Practice Proxies in Online Citizen Science. In 17th ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW 2014). https://doi.org/10.1145/2531602.2531721
. (2014). 
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.
. (2024). 
Motivations for sustained participation in crowdsourcing: The role of talk in a citizen science case study. In Proceedings of the Forty-eighth Hawai'i International Conference on System Sciences (HICSS-48).
. (2015). 
Motivation and data quality in a citizen science game: A design science evaluation. In Forty-sixth Hawai'i International Conference on System Sciences (HICSS-46). Presented at the Forty-sixth Hawai'i International Conference on System Sciences (HICSS-46), Wailea, HI.
. (2013). 
Linguistic adoption in online citizen science: A structurational perspective. In International Conference on Information Systems. Retrieved de https://aisel.aisnet.org /icis2019/crowds_social/crowds_social/28/
. (2019). 
Levels of trace data for social and behavioural science research. In , Big Data Factories: Collaborative Approaches. https://doi.org/10.1007/978-3-319-59186-5_4
. (2017). 
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). 
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). 
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). The Hermeneutics of Trace Data: Building an Apparatus. In IFIP Working Group 8.2 Working Conference.
. (2016). 
“Guess what! You’re the first to see this event”: Increasing Contribution to Online Production Communities. In ACM Group. https://doi.org/10.1145/2957276.2957284
. (2016). 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: 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).