@proceedings {9999,
	title = {Linguistic adoption in online citizen science: A structurational perspective},
	year = {2019},
	address = {Munich, Germany},
	abstract = {<p>For peer-production projects to be successful, members must develop a specific and common language that enables them to cooperate. We address the question of what factors affect the development of shared language in open peer production communities? Answering this question is important because we want the communities to be productive even when self-managed, which requires understanding how shared language emerges. We examine this question using a structurational lens in the setting of a citizen science project. Examining the use of words in the Gravity Spy citizen science project, we find that many words are reused and that most novel words that are introduced are not picked up, showing reproduction of structure. However, some novel words are used by others, showing an evolution of the structure. Participants with roles closer to the science are more likely to have their words reused, showing the mutually reinforcing nature of structures of signification, legitimation and domination.</p>},
	url = {https://aisel.aisnet.org /icis2019/crowds_social/crowds_social/28/},
	attachments = {https://citsci.syr.edu/sites/crowston.syr.edu/files/Linguistic\%20Adoption\%20\%28ICIS\%29\%20final.pdf},
	author = {Corey Brian Jackson and Carsten {\O}sterlund and Mahboobeh Harandi and Dhruv Kharwar and Kevin Crowston}
}
@inbook {9999,
	title = {Levels of trace data for social and behavioural science research},
	booktitle = {Big Data Factories: Collaborative~Approaches},
	year = {2017},
	publisher = {Springer Nature},
	organization = {Springer Nature},
	abstract = {<p>The explosion of data available from online systems such as social media is creating a wealth of trace data, that is, data that record evidence of human activity. The volume of data available offers great potential to advance social and behavioural science research. However, the data are of a very different kind than more conventional social and behavioural science data, posing challenges to use. This paper adopts a data framework from Earth Observation science and applies it to trace data to identify possible issues in analyzing trace data. Application of the framework also reveals issues for sharing and reusing data.</p>},
	isbn = {978-3-319-59186-5},
	doi = {10.1007/978-3-319-59186-5_4},
	attachments = {https://citsci.syr.edu/sites/crowston.syr.edu/files/160529\%20levels\%20book\%20chapter_0.pdf},
	author = {Kevin Crowston},
	editor = {Sorin Matei and Sean Goggins and Nicolas Jullien}
}
@conference {2013,
	title = {Learning at the Seafloor, Looking at the Sky: The Relationship Between Individual Tasks and Collaborative Engagement in Two Citizen Science Projects},
	booktitle = {Computer Supported Collaborative Learning },
	year = {2013},
	attachments = {https://citsci.syr.edu/sites/crowston.syr.edu/files/CSCL\%202013\%20Poster\%20Final.pdf , https://citsci.syr.edu/sites/crowston.syr.edu/files/Posterv2.pdf},
	author = {Katie DeVries Hassman and Gabriel Mugar and Carsten {\O}sterlund and Corey Jackson}
}
