- Level
- Undergraduate and graduate (cross-listed)
- Prerequisites
- None formal. Some experience with data collection (web scraping or APIs), quantitative analysis, and data visualization helps. Python or R helps but is not required.
- Length
- 15 weeks, two 75-minute meetings a week
- Tools
- Python and Jupyter (Anaconda); students can use R or other software
- Taught
- 2 terms, Fall 2016 and Fall 2018
- License
- CC BY-NC-SA 4.0
Overview
Online Collaboration is a research seminar on the social and technical mechanisms that make online collaboration systems such as Wikipedia work. How social processes and technical structures combine to make new kinds of interaction possible is a central question in information science, and the course takes it apart as four smaller questions. (1) How does the design of an online collaboration system use basic social, psychological, and organizational processes? (2) What are the historical predecessors of cooperative social systems, and how do their lessons apply to online systems? (3) What behavioral data can researchers collect and analyze from these systems? (4) How can the success or failure of these systems inform the design of other incentive and governance models?
I taught it as a cross-listed seminar for undergraduate (INFO 3501) and graduate (INFO 5501) students. It belongs to the “Investigations in Information Science” series, which brings current research into the classroom as project-based investigations. There are no formal prerequisites. Students do better if they have some earlier experience with data collection, quantitative analysis, and data visualization, whether it came from a class, a research project, an internship, or an online course.
When I designed the course, I borrowed from three similar ones: Joseph Reagle’s “Online Communities” (Northeastern University), Aaron Shaw’s “Online Communities and Crowds” (Northwestern University), and Benjamin Mako Hill’s “Interpersonal Media” (University of Washington).
Learning objectives
- Discuss and compare the social processes in different online collaboration systems.
- Identify and collect the data that these systems generate.
- Design exploratory research with these data and interpret the findings.
- Propose and evaluate whether online collaboration can expand into other social, cultural, economic, and political areas.
Topics
The course has four modules, and each one ends with a module assignment. Predecessors starts with the history of commons and cooperatives, and Fundamentals covers the values, history, economics, and culture of the open source movement. Examples compares collective intelligence, peer production, crowdsourcing, creative collaboration, and distributed ledgers. Consequences turns to remix and viral culture, abuse and safety, and hacktivism and slacktivism. A meeting can be a lecture, a discussion, an activity, or a lab, depending on what the week needs.
| Week | Module | Topic |
|---|---|---|
| 1 | Predecessors | Introduction: cooperation, coordination, and collaboration |
| 2 | Predecessors | Commons and enclosures |
| 3 | Predecessors | Cooperativism and collective action |
| 4 | Fundamentals | Values in design |
| 5 | Fundamentals | History of open source |
| 6 | Fundamentals | Economics of open source |
| 7 | Fundamentals | Culture of open source |
| 8 | Examples | Collective intelligence |
| 9 | Examples | Peer production |
| 10 | Examples | Crowdsourcing |
| 11 | Examples | Creative collaboration |
| 12 | Examples | Distributed ledgers |
| 13 | Consequences | Remixing and virality |
| 14 | Consequences | Abuse and safety |
| 15 | Consequences | Hacktivism and slacktivism |
Readings
The required book is Kraut and Resnick, Building Successful Online Communities: Evidence-Based Social Design (MIT Press, 2012). Each week also had magazine articles, research papers, and book chapters, plus optional readings for students who wanted more depth for a research project or for preliminary exams.
The module assignments ask students to collect online data, so the class also reads these guides to research ethics:
- Association for Computing Machinery, ACM Code of Ethics and Professional Conduct
- Association of Internet Researchers, ethics working committee reports
- American Psychological Association, report on psychological research online
Assignments and assessment
| Assignment | Share of grade |
|---|---|
| Module assignments | 55% |
| Participation | 30% |
| Weekly discussion | 15% |
Module assignments come at the end of each of the four modules, and each one is a report of about 10 pages. The class and I work out the format and the weight of each assignment together.
Participation counts attendance at the 30 class meetings and active engagement: respectful interaction, good preparation, curiosity, and connections to themes from earlier classes or other courses.
The weekly discussion is a prompt to reflect on the week’s readings, activities, and lectures. Students also reply to each other’s responses.
Adopt this course
Any scripting or statistical software works. The in-class examples and solutions are Jupyter notebooks in Python, with the Anaconda distribution of Python.
Students collect public data from online collaboration systems and online communities. They follow each site’s terms of service and privacy policy, collect only public data, identify themselves as students or researchers when they interact with others, and remove participants from their study on request.
There is no public repository. The labs, tutorials, and data for Fall 2018 were on the course’s learning management system.
The topics fill a 15-week semester with two meetings a week, 30 meetings in all. In a shorter term, I would drop one or two weeks from the Examples module. The material on this page is under CC BY-NC-SA 4.0; the required book is under the publisher’s copyright.
Past offerings
I first taught the course in Fall 2016 as a seminar on peer production and crowdsourcing, and in Fall 2018 I rebuilt it as a four-module seminar on online collaboration.
| Term | Design | Materials |
|---|---|---|
| Fall 2016 | “Problems in Information Science: Peer Production and Crowdsourcing”: reading responses (30%), labs (30%), a final project (25%), and participation (15%) | — |
| Fall 2018 | “Investigations in Information Science: Online Collaboration”: the design on this page | — |
Course materials on this page are licensed under CC BY-NC-SA 4.0: reuse and adapt them with credit, not for commercial use, and share adaptations under the same license. Last reviewed October 8, 2026.