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=== University of Washington Courses === | === University of Washington Courses === | ||
* '''[Fall 2021]''' '''[[DUB Seminar (Fall 2021)|HCID590: Design, Use, Build (DUB) Seminar]]''' — A | * '''[Fall 2021]''' '''[[Professional Development Proseminar: Funding for Teaching and Research (Fall 2021)|COM594 Professional Development Proseminar: Funding for Teaching and Research (Fall 2021)]]''' — A one-credit course on grants and funding that is part of the UW MA/PhD program's professional development proseminar series. Taught by [[User:Mako|Benjamin Mako Hill]]. | ||
* '''[Fall 2021]''' '''[[DUB Seminar (Fall 2021)|HCID590: Design, Use, Build (DUB) Seminar]]''' — A one-credit course in the [https://mhcid.washington.edu/ MHCI+D program at UW] built around the [https://dub.washington.edu/seminar.html DUB Seminar] speakers series. Taught by [[User:Mako|Benjamin Mako Hill]]. | |||
== Public Data Science Workshops == | == Public Data Science Workshops == | ||
Revision as of 20:06, 3 October 2021
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:
- Dr. Yoel Roth: Online Safety and Security
- On Oct. 23, 2024, Dr. Yoel Roth gave a lecture titled as “Decentralizing online safety and security: The promises and perils of federated social media” hosted by the Department of Human-Centered Design and Engineering at University of Washington, and a number of CDSC faculty and students were present and discussed issues of digital governance with …
Continue reading "Dr. Yoel Roth: Online Safety and Security"
- — madisondeyo 2024-11-09
- FOSSY 2024 Wrap Up: Sophia Vargas on “A review of valuation models and their application to open source models”
- In the seventh talk of the Science of Community track we organized for FOSSY, Google FOSS researcher Sophia Vargas offered an overview of different strategies for measuring the value of open source (particularly in the context of a company thinking about how to engage with FOSS). Some of Sophia’s key insights are: models for measuring …
- — kaylea 2024-10-15
- Check Out the PhD Q&A Session!
- Missed the prospective student Q&A session? Fear not, you can still hear from our faculty members, see a few examples of current students research, and listen to answers for our prospective student audience. You can find more resources about the Community Data Science Collective below: Still have questions for our group? Check out our people …
- — madisondeyo 2024-10-23
- FOSSY 2024 Wrap Up: Darius Kazemi on “Community governance models on small-to-mid-size Mastodon servers
- In the sixth talk of the Science of Community track we organized for FOSSY, independent FOSS researcher Darius Kazemi described the results of an interview study to learn from the moderation teams of decentralized social network servers. One of Darius’ key observations is the extensive compliance and legally-required work that running such a server requires. …
- — kaylea 2024-10-14
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] Introduction to Graduate Research (MTS 501, Fall, 2021) – The goal of this seminar is to introduce first-year students in the Northwestern University TSB and MTS Ph.D. programs to (1) current research in these fields, and (2) key challenges involved in pursuing an impactful, 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
- [Fall 2021] COM594 Professional Development Proseminar: Funding for Teaching and Research (Fall 2021) — A one-credit course on grants and funding that is part of the UW MA/PhD program's professional development proseminar series. Taught by Benjamin Mako Hill.
- [Fall 2021] HCID590: Design, Use, Build (DUB) Seminar — A one-credit course in the MHCI+D program at UW built around the DUB Seminar speakers series. Taught by Benjamin Mako Hill.
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.
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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 <math> tags like this: <math>\frac{\sigma}{\sqrt{n}}</math> and it will write .
