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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.

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.

To learn more about the CDSC, please check out our about page (especially the links there). Prospective students should also review these materials.

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

[Summer 2023] Advanced Computational Communication Methods – In this class, we will investigate a number of more advanced methods or concepts not covered in the Intro to Programming and Data Science course, including SQL, computational text analysis, creating reproducible projects, and advanced visualization.

[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

[Spring 2024] COM 481: Online Communities — A course on online communities taught by Kaylea Champion.

Public Data Science Workshops

Click here for details and to sign up for announcements about upcoming Community Data Science Workshops in Seattle.

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 ${\frac {\sigma }{\sqrt {n}}}$ .

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 …
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 …
Continue reading "FOSSY 2024 Wrap Up: Sophia Vargas on “A review of valuation models and their application to open source models”"; — 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 …
Continue reading "Check Out the PhD Q&A Session!"; — 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. …
Continue reading "FOSSY 2024 Wrap Up: Darius Kazemi on “Community governance models on small-to-mid-size Mastodon servers"; — 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 …
Continue reading "FOSSY 2024 Wrap Up: Bogdan Vasilescu on “Navigating Dependency Abandonment”"; — kaylea 2024-10-21

@@ Line 1: / Line 1: @@
-{{Banner}}
 __NOTOC__
-[[File:CDSC at Pok Pok (2017-03).jpg|250px|thumb|right|[[People|CDSC members]] at Pok Pok in March 2017. Clockwise from top left: Sneha, Mako, Aaron, Emilia, Nate, Jeremy, Sayamindu, Salt.]]
+The '''Community Data Science Collective''' is an interdisciplinary research group made up of faculty and students at the [http://www.com.washington.edu/ University of Washington Department of Communication], the [https://communication.northwestern.edu/academics/communication-studies/ Northwestern University Department of Communication Studies], the [https://www.carleton.edu/computer-science/ Carleton College Computer Science Department], and the [https://www.cla.purdue.edu/academic/communication/ Purdue University School of Communication].
+<div class="row">
+<div class="col-md-9">
+<div class="res-box">
+[[File:CDSC_group_photo-20230923-fun.jpg|thumb|1741px|[[People|CDSC members]] at the CDSC group retreat in September 2023 in Evanston. Check out our other [[group photos]]!]]
+</div>
-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].
 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.
@@ Line 12: / Line 16: @@
 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.
-== Workshops and Courses ==
+To learn more about the CDSC, please check out our [[About|about page]] (especially the links there). Prospective students should also review [[CommunityData:Prospective_students|these materials]].
-In addition to research, we run workshops and teach classes. 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.
+== Courses ==
-=== Public Data Science Workshops ===
+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.
+<!-- === Northwestern Courses === -->
-'''[[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 roughly twice a year since beginning in Seattle in 2014. 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.
+=== Purdue Courses ===
-<gallery mode="packed-overlay" heights="100px">
+* '''[Summer 2023]''' '''[[Advanced Computational Communication Methods (Summer 2023) | Advanced Computational Communication Methods]]''' &ndash; In this class, we will investigate a number of more advanced methods or concepts not covered in the Intro to Programming and Data Science course, including SQL, computational text analysis, creating reproducible projects, and advanced visualization.
-Community_Data_Science_Workshops_(Spring_2015)_at_University_of_Washington_34.jpg
-Community_Data_Science_Workshops_(Spring_2015)_at_University_of_Washington_14.jpg
-Community_Data_Science_Workshops_(Spring_2015)_at_University_of_Washington_19.jpg
-Community_Data_Science_Workshops_(Spring_2015)_at_University_of_Washington_36.jpg
-</gallery>
-=== University of Washington Courses ===
+* '''[Spring 2023]''' '''[[Quantitative_Methods_for_Communication_(Spring_2023) | Quantitative Methods for Communication]]''' &ndash; 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.
-* '''[Fall 2017]''' '''[[HCDS (Fall 2017)|DATA512: Human Centered Data Science]]''' — Fundamental principles of data science and its human implications. Data ethics; data privacy; differential privacy; algorithmic bias; legal frameworks and intellectual property; provenance and reproducibility; data curation and preservation; user experience design and usability testing for big data; ethics of crowdwork; data communication; and societal impacts of data science.
+<!--
+* '''[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 2017]''' '''[[Innovation Communities (Spring 2017)|COM597: Innovation Communities]]''' — A [http://http://commlead.washington.edu/ UW Communication Leadership’s] elective in the “Masters in Communication in Communities and Networks” program covering using online communities to harness user innovation taught by [[User:Benjamin Mako Hill|Benjamin Mako Hill]].
+* '''[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]].
+-->
-=== Northwestern Courses & Workshop ===
+=== University of Washington Courses ===
-* '''[[BYOR|Bring Your Own Research Workshop (BYOR)]]''' — A research workshop for CDSC affiliates and fellow travelers at Northwestern convened by [[User:Aaronshaw|Aaron Shaw]]. Participants present work and provide peer feedback/accountability in weekly meetings. Most members of the group are affiliates of the [http://mts.northwestern.edu Media, Technology & Society] and [http://tsb.northwestern.edu Technology & Social Behavior] programs at Northwestern and study online communities, collective action, organizations, collaboration, and related topics.
-== Research Resources ==
+* '''[Spring 2024]''' [[Online Communities (UW COM481 Spring 2024)|COM 481: Online Communities]]''' — A course on online communities taught by [[User:Kaylea|Kaylea Champion]].
-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.
+== Public Data Science Workshops ==
+{{banner}}
-== Research News ==
+'''[[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.
-Follow us as [https://twitter.com/comdatasci @comdatasci on Twitter] and subscribe to the [https://blog.communitydata.cc/ Community Data Science Collective blog].
+<gallery mode="packed-overlay" heights="100px">
+Community_Data_Science_Workshops_(Spring_2015)_at_University_of_Washington_34.jpg
+Community_Data_Science_Workshops_(Spring_2015)_at_University_of_Washington_14.jpg
+Community_Data_Science_Workshops_(Spring_2015)_at_University_of_Washington_19.jpg
+Community_Data_Science_Workshops_(Spring_2015)_at_University_of_Washington_36.jpg
+</gallery>
-Recent posts from the blog include:
+== Research Resources ==
-<rss max=4 date="Y-m-d">https://blog.communitydata.cc/feed/atom/</rss>
+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==
@@ Line 56: / Line 63: @@
 * There's a CAPTCHA enabled. If you create an account and then contact any [[People|collective member]] with the username (on or off wiki), they can turn the CAPTCHA off for you.
-* [https://www.mediawiki.org/wiki/Extension:Math Extension:Math] is installed so you can write math here. Basically you just add math by putting TeX inside <nowiki><nowiki></nowiki> tags like this: <nowiki><math>\frac{\sigma}{\sqrt{n}}</math></nowiki>
+* [https://www.mediawiki.org/wiki/Extension:Math Extension:Math] is installed so you can write math here. Basically you just add math by putting TeX inside <nowiki><math></nowiki> tags like this: <nowiki><math>\frac{\sigma}{\sqrt{n}}</math></nowiki> and it will write <math>\frac{\sigma}{\sqrt{n}}</math>.
+</div>
+<div class="col-md-3" style="font-size: 80%;">
+<h3>Research News</h3>
+Follow us as [https://twitter.com/comdatasci @comdatasci on Twitter] and [https://social.coop/@communitydata @communitydata@social.coop in the Fediverse/Mastodon] and subscribe to the [https://blog.communitydata.science/ Community Data Science Collective blog].
+Recent posts from the blog include:
+<rss max=5 date="Y-m-d">https://blog.communitydata.science/feed/atom/</rss>
+</div>
+</div>