Stanford Seminar - Online communities as model systems for commons governance

May 10, 2024
Seth Frey, UC Davis

The best citizens of a large-scale democracy are those who have built and broken several small ones to see how they work. By empowering people to build any kind of community together, the Internet has become a laboratory for self-governance experimentation. Groups who start online communities must overcome the challenges of recruiting finite resources around difficult common goals. Fortunately, they can draw on a growing range of support technologies, peer networks, and scholarship. With their transparency, the Internet's millions of online communities can be surveyed for insights into their design and functioning. Looking at three large platforms for small self-governing online communities, we will pose several questions of institutional processes at the population level, as drawn from the literatures on common-pool resource management and institutional analysis and design.

About the speaker:
Dr. Seth Frey is a computational social scientist who studies commons governance institutions and other complex social systems. He specializes in using online communities as model systems for emergent institutional and organizational phenomena. His expertise is in computational approaches to self-governance and the cognitive science of strategic behavior.

He is an associate professor in Communication at the University of California Davis, an affiliate of the Ostrom Workshop at Indiana University, and a Research Director at Metagov. He was a behavioral economist at Disney Research in Walt Disney Imagineering, and a complex systems scholar at NECSI. Seth earned his Ph.D. in Cognitive Science and Informatics (complex systems) at Indiana University in 2013, and a B.A. in Cognitive Science from UC Berkeley.

Seth's research has appeared in PNAS, Nature Scientific Reports, and Proceedings of the Royal Society. It has been covered in The New Yorker, New York Times Magazine, and TEDx. It has been funded by the NSF, NASA, and the Ford Foundation.

More about the course can be found here: https://hci.stanford.edu/seminar/

View the entire CS547 Stanford Human-Computer Interaction Seminar playlist: https://www.youtube.com/playlist?list=PLoROMvodv4rMyupDF2O00r19JsmolyXdD

► Check out the entire catalog of courses and programs available through Stanford Online: https://online.stanford.edu/explore Receive SMS online on sms24.me

Watch on YouTube

Subscribe on YouTubeReaderBot

TubeReader video aggregator is a website that collects and organizes online videos from the YouTube source. Video aggregation is done for different purposes, and TubeReader take different approaches to achieve their purpose.

Our try to collect videos of high quality or interest for visitors to view; the collection may be made by editors or may be based on community votes.

Another method is to base the collection on those videos most viewed, either at the aggregator site or at various popular video hosting sites.

TubeReader site exists to allow users to collect their own sets of videos, for personal use as well as for browsing and viewing by others; TubeReader can develop online communities around video sharing.

Our site allow users to create a personalized video playlist, for personal use as well as for browsing and viewing by others.

@YouTubeReaderBot allows you to subscribe to Youtube channels.

By using @YouTubeReaderBot Bot you agree with YouTube Terms of Service.

Use the @YouTubeReaderBot telegram bot to be the first to be notified when new videos are released on your favorite channels.

Look for new videos or channels and share them with your friends.

You can start using our bot from this video, subscribe now to Stanford Seminar - Online communities as model systems for commons governance

What is YouTube?

YouTube is a free video sharing website that makes it easy to watch online videos. You can even create and upload your own videos to share with others. Originally created in 2005, YouTube is now one of the most popular sites on the Web, with visitors watching around 6 billion hours of video every month.