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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, the Northwestern University Department of Communication Studies, the University of North Carolina School of Information and Library Science, the Carleton College Computer Science Department, and the Purdue University School of Communication.



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.

Research News
Follow us as @comdatasci on Twitter and subscribe to the Community Data Science Collective blog.

Recent posts from the blog include:

https://blog.communitydata.science/feed/atom/

Courses
In addition to research, we teach classes and run workshops. Some of that work is coordinated on this wiki. A more detailed lists of workshops and teaching material on this wikis is on our Workshops and Classes page. In this page, we only list ongoing classes and workshops.

Northwestern Courses

 * [Fall 2021] MTS 501—Introduction to Graduate Research (Fall, 2021) – The goal of this seminar is to introduce first-year students in the MTS and TSB Ph.D. programs to (1) current research in these fields, and (2) key challenges involved in pursuing a productive, responsible, and fulfilling research career. Taught by Aaron Shaw

Purdue University

 * [Fall 2021] Communication and Social Networks (COM 411, Fall 2021) – This class focuses on understanding how the structure of relationships between people influence communication patterns and behavior. This perspective can help us to understand a broad set of phenomena, from online communities to friendships to businesses. The course will also introduce students to using network visualizations to gain and share insights about network phenomena. Taught by Jeremy Foote.
 * [Fall 2021] Intro to Programming and Data Science (COM 674, Fall 2021) – This course is intended to give students an introduction to programming principles, the Python programming language, and data science tools and approaches. Taught by Jeremy Foote.

University of Washington Courses

 * [Winter 2021] COM520: Statistical Methods in Communication — 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. Taught by Benjamin Mako Hill.
 * [Winter 2021] COM482: Interpersonal Media: Online Communities — A course on online communities and computer mediated communication with an emphasis on learning from research in social psychology, sociology, and behavioral economics taught by Nathan TeBlunthuis.
 * [Winter 2021] Directed Research Group: The COVID-19 Information Landscape (Winter 2021) — A directed research group studying our response to the Coronavirus/Covid-19 pandemic.

Public Data Science 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 six times in Seattle between 2014 and 2020. So far, more than 100 people have volunteered their weekends to teach more than 500 people to program in Python, to build datasets from Web APIs, and to ask and answer questions using these data.

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.

About 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.

This is mostly a normal MediaWiki although there are a few things to know:


 * There's a CAPTCHA enabled. If you create an account and then contact any collective member with the username (on or off wiki), they can turn the CAPTCHA off for you.
 * Extension:Math is installed so you can write math here. Basically you just add math by putting TeX inside tags like this: $$\frac{\sigma}{\sqrt{n}}$$ and it will write $$\frac{\sigma}{\sqrt{n}}$$.