We’re going to be at CHI! The Community Data Science Collective will be presenting three papers. You can find us there in person in New Orleans, Louisiana, April 30 – May 5. If you’ve ever wanted a super cool CDSC sticker, this is your chance!
This winter, the Community Data Science Collective launched a Community Dialogues series. These are meetings in which we invite community experts, organizers, and researchers to get together to share their knowledge of community practices and challenges, recent research, and how that research can be applied to support communities. We had our first meeting in February, with presentations from Jeremy Foot and Sohyeon Hwang on small communities and Nate TeBlunthius and Charlie Keine on overlapping communities.
Here are some quick summaries of the presentations. After the presentations, we formed small groups to discuss how what we learned related to our own experiences and knowledge of communities.
Finding Success in Small Communities
Small communities often stay small, medium stay medium, and big stay big. Meteoric growth is uncommon. User control and content curation improves user experience. Small communities help people define their expectations. Participation in small communities is often very salient and help participants build group identity, but not personal relationships. Growth doesn’t mean success, and we need to move beyond that and solely using quantitative metrics to judge our success. Being small can be a feature, not a bug!
We built a list of discussion questions collaboratively. It included:
Are you actively trying to attract new members to your community? Why or why not?
How do you approach scale/size in your community/communities?
Do you experience pressure to grow? From where? Towards what end?
What kinds of connections do people seek in the community/communities you are a part of?
Can you imagine designs/interventions to draw benefits from small communities or sub-communities within larger projects/communities?
How to understand/set community members’ expectations regarding community size?
“Small communities promote group identity but not interpersonal relationships.” This seems counterintuitive.
How do you managing challenges around growth incentives/pressures?
Why People Join Multiple Communities
People join topical clusters of communities, which have more mutualistic relationships than competitive ones. There is a trilemma (like a dilemma) between large audience, specific content, and homophily (likemindness). No community can do everything, and it may be better for participants and communities to have multiple, overlapping spaces. This can be more engaging, generative, fulfilling, and productive. People develop portfolios of communities, which can involve many small communities..
Questions we had for each other:
Do members of your community also participate in similar communities?
What other communities are your members most often involved in?
Are they “competing” with you? Or “mutualistic” in some way?
In what other ways do they relate to your community?
There is a “trilemma” between the largest possible audience, specific content, and homophilous (likeminded/similar folks) community. Where does your community sit inside this trilemma?
Thanks to speakers Charlie Kiene, Jeremy Foote, Nate TeBlunthius, and Sohyeon Hwang! Kaylea Champion was heavily involved in planning and decision making. The vision for the event borrows from the User and Open Innovation workshops organized by Eric von Hippel and colleagues, as well as others. This event and the research presented in it were supported by multiple awards from the National Science Foundation (DGE-1842165; IIS-2045055; IIS-1908850; IIS-1910202), Northwestern University, the University of Washington, and Purdue University.
Session summaries and questions above were created collaboratively by event attendees.
This year was packed with things we’re excited about and want to celebrate and share. Great things happened to Community Data Science Collective members within our schools and the wider research community.
Salt was interviewed on the FOSS and Crafts podcast. His conference presentations included Linux App Summit, SeaGL and DebConf. Kaylea Champion spoke at SeaGL and DebConf. Kaylea’s DebConf present was on her research on detecting at-risk projects in Debian.
Champion, Kaylea. 2021. “Underproduction: An approach for measuring risk in open source software.” 28th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER). pp. 388-399, doi: 10.1109/SANER50967.2021.00043.
Fiers, Floor , Aaron Shaw , and Eszter Hargittai. 2021. “Generous Attitudes and Online Participation.” Journal of Quantitative Description: Digital Media, 1. https://doi.org/10.51685/jqd.2021.008
Hill, Benjamin Mako , and Aaron Shaw , 2021. “The hidden costs of requiring accounts: Quasi-experimental evidence from peer production.” Communication Research 48(6): 771-795. https://doi.org/10.1177%2F0093650220910345.
Hwang, Sohyeon and Jeremy Foote . 2021. “Why do people participate in small online communities?”. Proceedings of the ACM on Human-Computer Interaction, 5(CSCW2), 462:1-462:25. https://doi.org/10.1145/3479606
Shaw, Aaron and Eszter Hargittai. 2021. “Do the Online Activities of Amazon Mechanical Turk Workers Mirror Those of the General Population? A Comparison of Two Survey Samples.” International Journal of Communication 15: 4383–4398. https://ijoc.org/index.php/ijoc/article/view/16942
TeBlunthuis, Nathan , Benjamin Mako Hill , and Aaron Halfaker. 2021. “Effects of Algorithmic Flagging on Fairness: Quasi-experimental Evidence from Wikipedia.” Proc. ACM Hum.-Comput. Interact. 5, CSCW1, Article 56 (April 2021), 27 pages. https://doi.org/10.1145/3449130
TeBlunthuis, Nathan. 2021 “Measuring Wikipedia Article Quality in One Dimension.” In Proceedings of the 17th International Symposium on Open Collaboration (OpenSym ’21). Online: ACM Press. https://doi.org/10.1145/3479986.3479991.
Thinking about applying to graduate school? Wonder what it’s like to pursue a PhD? Interested in understanding relationships between technology and society? Curious about how to do research on online communities like Reddit, Wikipedia, or GNU/Linux? The Community Data Science Collective is hosting a Q&A on November 5th at 13:00 ET / 12:00 CT / 10:00 PT for prospective students. This session is scheduled for an hour, to be divided between a larger group session with faculty and then smaller groups with current graduate students.
This is an opportunity for prospective grad students to meet with CDSC faculty, students, and staff. We’ll be there to answer any questions you have about the group, the work we do, your applications to our various programs, and other topics. You can either submit a question ahead of time or ask one during the session.
About the CDSC
We are an interdisciplinary research group spread across Carleton, Northwestern University, Purdue University, and the University of Washington. (Carleton is not accepting graduate students, though the other universities are.) You can read more about PhD opportunities on our blog.
We are mostly quantitative social scientists pursuing research about the organization of online communities, peer production, online communities, and learning and collaboration in social computing systems. Our group research blog and publications page can tell you more about our work.
Notes About Attending
We are so excited to meet you! Please RSVP online to let us know if you’re coming. This form also gives you the opportunity to ask a question ahead of time. By doing this, we’ll be able to make sure we get to your questions.
We will post another announcement with attendance information. We will also email attendance details to all registered attendees.