Difference between revisions of "Main Page"

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Welcome to the wiki for the [[Community Data Science Collective]]. It is open to the public and hackable by all but mostly contains information that will be useful to collective members, their collaborators, people enrolled in their projects, or people interested in building off of their work. If you're interested in making a change or creating content here, generally feel empowered to [[:w:WP:BOLD|Be Bold]]. If things don't fit, somebody who watches this wiki will be in touch.
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The [[Community Data Science Collective]] is an interdisciplinary research group made of up of faculty and students at the [http://www.com.washington.edu/ University of Washington Department of Communication] and the [http://www.communication.northwestern.edu/departments/communicationstudies/ Northwestern University Department of Communication Studies].
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We are social scientists applying a range of quantitative and qualitative methods to the study of online communities. We seek to understand both how and why some attempts at collaborative production — like Wikipedia and Linux — build large volunteer communities and high quality work products.
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Our research is particularly focused on how the design of communication and information technologies shape fundamental social outcomes with broad theoretical and practical implications — like an individual’s decision to join a community, contribute to a public good, or a group’s ability to make decisions democratically.
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Our research is deeply interdisciplinary, most frequently consists of “big data” quantitative analyses, and lies at the intersection of communication, sociology, and human-computer interaction.
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The group is led by [http://mako.cc/academic/ Benjamin Mako Hill] and [http://aaronshaw.org/ Aaron Shaw].
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=== Recent Blog Posts ===
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<rss max=4 date="Y-m-d">https://blog.communitydata.cc/feed/atom/</rss>
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== This Wiki==
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This is open to the public and hackable by all but mostly contains information that will be useful to collective members, their collaborators, people enrolled in their projects, or people interested in building off of their work. If you're interested in making a change or creating content here, generally feel empowered to [[:w:WP:BOLD|Be Bold]]. If things don't fit, somebody who watches this wiki will be in touch.
  
 
== Public Workshops ==
 
== Public Workshops ==

Revision as of 21:58, 20 January 2017


The Community Data Science Collective is an interdisciplinary research group made of up of faculty and students at the University of Washington Department of Communication and the Northwestern University Department of Communication Studies.

We are social scientists applying a range of quantitative and qualitative methods to the study of online communities. We seek to understand both how and why some attempts at collaborative production — like Wikipedia and Linux — build large volunteer communities and high quality work products.

Our research is particularly focused on how the design of communication and information technologies shape fundamental social outcomes with broad theoretical and practical implications — like an individual’s decision to join a community, contribute to a public good, or a group’s ability to make decisions democratically.

Our research is deeply interdisciplinary, most frequently consists of “big data” quantitative analyses, and lies at the intersection of communication, sociology, and human-computer interaction.

The group is led by Benjamin Mako Hill and Aaron Shaw.

Recent Blog Posts

Forming, storming, norming, performing, and …chloroforming?
In 1965, Bruce Tuckman proposed a “developmental sequence in small groups.” According to his influential theory, most successful groups go through four stages with rhyming names: Forming: Group members get to know each other and define their task. Storming: Through argument and disagreement, power dynamics emerge and are negotiated. Norming: After conflict, groups seek to …

— Jeremy Foote

http://www.jeremydfoote.com 2018-06-26
Summer Institute in Computational Social Science
For the second year, Matt Salganik and Chris Bail are running a two-week Summer Institute in Computational Social Science at Duke Univeristy. The goal of the institute is to bring social scientists and data scientists together to learn about computational social science, which can be described as a merger of their two fields. This year, …

— Jeremy Foote

http://www.jeremydfoote.com 2018-06-21
Sayamindu Dasgupta Joining the University of North Carolina Faculty
The School of Information and Library Sciences (SILS) at the University of North Carolina in Chapel Hill announced this week that the Community Data Science Collective’s very own Sayamindu Dasgupta will be joining their faculty as a tenure-track assistant professor. The announcement from SILS has much more detail and makes very clear that UNC is …

— Benjamin Mako Hill

http://mako.cc 2018-05-26
Community Data Science Collective at ICA 2018 in Prague
Jeremy Foote, Nate TeBlunthuis, and Mako Hill are in Prague this week for the  International Communication Association’s 2018 annual meeting. The collective has three things on the conference program this year: Fri, May 25, 9:30 to 10:45, Hilton Prague, LL, Vienna: An Agent-Based Model of Online Community Joining as part of the Computational Methods section …

— Benjamin Mako Hill

http://mako.cc 2018-05-26

This Wiki

This is open to the public and hackable by all but mostly contains information that will be useful to collective members, their collaborators, people enrolled in their projects, or people interested in building off of their work. If you're interested in making a change or creating content here, generally feel empowered to Be Bold. If things don't fit, somebody who watches this wiki will be in touch.

Public Workshops

Community Data Science Workshops — The Community Data Science Workshops (CDSW) are a series of workshops designed to introduce some of the basic tools of programming and analysis of data from online communities to absolute beginners. The CDSW have been held four times in Seattle in 2014 and 2015. So far, more than 80 people have volunteered their weekends to teach more than 350 people to program in Python, to build datasets from Web APIs, and to ask and answer questions using these data.

University of Washington Courses

  • [Winter 2017] COM521: Statistics and Statistical Programming — A quarter-long quantitative methods course that builds a first-quarter introduction to quantitative methodology and that focuses on both the more mathematical elements of statistics as well as the nuts-and-bolts of statistical programming in the GNU R programming language.

Northwestern Courses & Workshop

  • Online Communities & Crowds (COMMST 378, Fall 2016) — This advanced undergraduate course presents an interdisciplinary introduction to the study of online communities and crowds, with a particular emphasis on how and why some of these systems are so wildly effective at mobilizing and organizing people in ways that seem to have been impossible a few decades ago.
  • Introduction to Graduate Research (MTS 501, Fall 2016) — The first of two required seminars in the Media, Technology & Society (MTS) and Technology and Social Behavior (TSB) programs, this course introduces first year Ph.D. students to research skills and gives guidance on how to be a productive and responsible scholar.
  • The Practice of Scholarship (MTS 503, Spring 2016) — The second of two required seminars in the Media, Technology & Society (MTS) and Technology and Social Behavior (TSB) programs, the goal for this course is simple: submit a piece of academic research for publication by the end of the quarter. The course and assignments are structured to help students cultivate (more of) the skills, wisdom, and experience necessary to publish independent, original, and high-quality scholarship in relevant venues for their work. The experience will probably feel like a combination of a writing bootcamp and an extended group therapy session.

Research Resources

If you are a member of the collective, perhaps you're looking for CommunityData:Resources which includes details on email, TeX templates, documentation on our computing resources, etc.

License

Unless otherwise noted, everything on this wiki is freely available under the Creative Commons Attribution Share-Alike License so you should feel encouraged to build on and expand this content.