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=== Purdue Courses ===
=== Purdue Courses ===


* '''[Spring 2023]''' '''[[Community Data Science Course (Spring 2023) |COM597A/COMMLD570B: Community Data Science: Programming, Data Collection, and Data Science for Social Media]]''' — A quarter long course taught by [[User:Benjamin Mako Hill|Benjamin Mako Hill]] and [[User:Kaylea|Kaylea Champion]] that adapts and builds upon the [[CDSW]] curriculum to teach introductory programming, data collection, and basic data science tools to absolute beginners. The course is being offered jointly between the University of Washington Department of Communication's [https://com.uw.edu/graduate/ma-phd/ma-phd-overview/ MA/PhD program] and the [http://commlead.uw.edu/ Communication Leadership program].
* '''[Spring 2023]''' '''[[Quantitative_Methods_for_Communication_(Spring_2023) | Quantitative Methods for Communication]]''' – This course introduces students to a range of social-scientific research methods used to investigate human communication, with a focus on research design, statistics, and statistical software. Taught by [[User:Jdfoote|Jeremy Foote]] and Hazel Chiu.


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* '''[Fall 2022]''' '''[[Communication and Social Networks (Fall 2022)|Communication and Social Networks (COM 411, Fall 2022)]]''' &ndash; 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 [[User:Jdfoote|Jeremy Foote]].
* '''[Fall 2022]''' '''[[Communication and Social Networks (Fall 2022)|Communication and Social Networks (COM 411, Fall 2022)]]''' &ndash; 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 [[User:Jdfoote|Jeremy Foote]].


* '''[Fall 2022]''' '''[[Intro to Programming and Data Science (Fall 2022)|Intro to Programming and Data Science (COM 674, Fall 2022)]]'''  Taught by [[User:Jdfoote|Jeremy Foote]].
* '''[Fall 2022]''' '''[[Intro to Programming and Data Science (Fall 2022)|Intro to Programming and Data Science (COM 674, Fall 2022)]]'''  Taught by [[User:Jdfoote|Jeremy Foote]].
-->


=== University of Washington Courses ===
=== University of Washington Courses ===
* '''[Spring 2023]''' '''[[Community Data Science Course (Spring 2023) |COM597A/COMMLD570B: Community Data Science: Programming, Data Collection, and Data Science for Social Media]]''' — A quarter long course taught by [[User:Benjamin Mako Hill|Benjamin Mako Hill]] and [[User:Kaylea|Kaylea Champion]] that adapts and builds upon the [[CDSW]] curriculum to teach introductory programming, data collection, and basic data science tools to absolute beginners. The course is being offered jointly between the University of Washington Department of Communication's [https://com.uw.edu/graduate/ma-phd/ma-phd-overview/ MA/PhD program] and the [http://commlead.uw.edu/ Communication Leadership program].


* '''[Winter 2023]''' '''[[Online Communities (UW COM481 Winter 2023)|COM 481: Online Communities]]''' — A course on online communities taught by [[User:Kaylea|Kaylea Champion]].
* '''[Winter 2023]''' '''[[Online Communities (UW COM481 Winter 2023)|COM 481: Online Communities]]''' — A course on online communities taught by [[User:Kaylea|Kaylea Champion]].

Revision as of 12:40, 27 February 2023


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

CDSC members at the CDSC group retreat in October 2022 in Seattle. In a spiral starting from the top: Mako, Carl, Jeremy, Nick, Salt, Hazel, Yibin, Regina, Kaylea, Ellie, Aaron, Floor, Sohyeon, Molly, Emilia, Ryan, Charlie, Dyuti. Check out our other group photos!


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.

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 wiki is on our Workshops and Classes page. In this page, we only list ongoing classes and workshops.

Purdue Courses

  • [Spring 2023] Quantitative Methods for Communication – This course introduces students to a range of social-scientific research methods used to investigate human communication, with a focus on research design, statistics, and statistical software. Taught by Jeremy Foote and Hazel Chiu.


University of Washington Courses


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 <math> tags like this: <math>\frac{\sigma}{\sqrt{n}}</math> and it will write .

Research News

Follow us as @comdatasci on Twitter and @communitydata@social.coop in the Fediverse/Mastodon 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 …
— 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
FOSSY 2024 Wrap Up: Bogdan Vasilescu on “Navigating Dependency Abandonment”
In the final talk of the Science of Community track we organized for FOSSY, Computer Science professor and FOSS researcher Dr. Bogdan Vasilescu described his team’s work to understand how developers think about abandoned dependencies. One of the key insights from this work is that abandonment of dependencies is quite common, but that updating a …
— kaylea 2024-10-21