Main Page

From CommunityData
Revision as of 19:35, 20 July 2017 by Jdfoote (talk | contribs) (Public Data Science Workshops: typos)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to: navigation, search


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 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.

Workshops and Courses[edit]

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.

Public Data Science Workshops[edit]

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.

University of Washington Courses[edit]

Northwestern Courses & Workshop[edit]

Research Resources[edit]

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.

Research News[edit]

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

Recent posts from the blog include:

Testing Our Theories About Surviving an “Eternal September”
Last year at CHI 2016, we published a qualitative study examining the effects of a large influx of newcomers to the /r/nosleep online community in Reddit. Our study began with the observation that most research on sustained waves of newcomers focuses on the destructive effect of newcomers and frequently invokes Usenet’s infamous “Eternal September.” Our … Continue reading "Testing Our Theories About Surviving an “Eternal September”"
— charleskiene 2017-07-20
Learning to code in one’s own language
Millions of young people from around the world are learning to code. Often, during their learning experiences, these youth are using visual block-based programming languages like Scratch, App Inventor, and Code.org Studio. In block-based programming languages, coders manipulate visual, snap-together blocks that represent code constructs instead of textual symbols and commands that are found in … Continue reading "Learning to code in one’s own language"
— sayamindu 2017-06-27
The Community Data Science Collective Dataverse
I’m pleased to announce the Community Data Science Collective Dataverse. Our dataverse is an archival repository for datasets created by the Community Data Science Collective. The dataverse won’t replace work that collective members have been doing for years to document and distribute data from our research. What we hope it will do is get our … Continue reading "The Community Data Science Collective Dataverse"
— Benjamin Mako Hill http://mako.cc 2017-06-18
Adventures in onboarding new users on Wikipedia
I recently finished a paper that presents a novel social computing system called the Wikipedia Adventure. The system was a gamified tutorial for new Wikipedia editors. Working with the tutorial creators, we conducted both a survey of its users and a randomized field experiment testing its effectiveness in encouraging subsequent contributions. We found that although … Continue reading "Adventures in onboarding new users on Wikipedia"
— Sneha Narayan http://snehanarayan.com/ 2017-06-09


About This Wiki[edit]

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 <nowiki> tags like this: <math>\frac{\sigma}{\sqrt{n}}</math>