Date of Award
Summer 7-16-2021
Degree Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
School of Information Studies
Advisor(s)
Crowston, Kevin K. C.
Second Advisor
Kalish, Michael M. K.
Keywords
citizen science, crowdsourcing, groups
Subject Categories
Library and Information Science | Science and Technology Studies | Social and Behavioral Sciences
Abstract
Contributors to online crowdsourcing systems generally work independently on pieces of the product but in some cases, task interdependencies may require collaboration to develop a final product. These collaborations though take a distinctive form because of the nature of crowdsourced work. Collaboration may be implicit instead of explicit. Individuals engaged in a group conversation may not stay with the group for long, i.e., the group is an ``occasional group.'' Occasional group interactions are often not well supported by systems, as they are not designed for team work. This dissertation examines the characteristics and work of occasional groups in the Gravity Spy citizen science project. Occasional groups in this system form to reach agreement about the description of novel categories of data that volunteers identify in the system.
The author first employed virtual ethnography over six months to investigate volunteers' interactions and to identify features of the occasional groups in this setting. Most groups were transient, interacting only for a short time to develop one product, but a few worked together repeatedly.To describe the overall process of finding new categories brings individuals to work together, the author interviewed nine active volunteers about their work practices. Volunteers individually or collectively use tools such as hashtags, collections and a search tool to identify examples of a new category and to agree on a name and description.
Finally, the author investigated the details of the processes of developing proposals for four new categories over three years. She employed virtual and trace ethnography to collect messages from several discussion threads and boards to identify the analytical moves made by occasional group members in developing a new category. Volunteers would speculate on a new pattern and its causes, discuss how different categories are related and split or merge descriptions. They employed techniques such as detailed descriptions of data to create common ground, @-mention of other volunteers to increase the visibility of their work to each other and use of the category proposal as a vehicle to coordinate their actions.
Findings contribute to the group literature by recognizing that groups with no formal formation and work processes are capable of doing work that would not otherwise be possible. The results advance our understanding of group categorization literature by showing how the analytical moves are different when group members work occasionally. The thesis also provides some suggestions for better support of occasional groups in crowdsourcing platforms.
Access
Open Access
Recommended Citation
Harandi, Mahboobeh, "Occasional Groups in Crowdsourcing Platforms" (2021). Dissertations - ALL. 1525.
https://surface.syr.edu/etd/1525