The CrowdResearch.org blog, Follow the Crowd, intends to become the premier web resource for ideas related to crowd computing research. Our focus is rapid dissemination of these ideas and vigorous discussion of them.
Please do not hesitate to send the editors questions, suggestions, or feedback at firstname.lastname@example.org. We would love to hear from you!
Our audience is anyone interested in crowd computing research who is too busy to go to all the conferences and read all the journals. This audience spans disciplines (e.g., computer science, AI, HCI, economics, law) and roles (e.g., students, faculty, academic, industry, government, enterprise, startup, crowd workers).
Essentially, crowd computing involves systems where groups of people work together, both with each other and with computers, to do something smart. This includes but isn’t limited to:
- computer-mediated mass collaboration (e.g., wikis)
- crowd data mining
- wisdom of the crowds by computational methods (e.g., prediction markets)
- computational models of group search or problem solving
- technologies for making groups smarter
- ethics of crowd computing
- mass communication and collaboration
Similar or synonymous terms include: human computation, crowdsourcing, collective intelligence, and sometimes social computing.
What we publish
Our scope includes but is not limited to the following types of posts:
- Summaries of papers from peer-reviewed workshops, conferences, and journals (either recent or upcoming)
- Micro-surveys, i.e., critical summaries of groups of such papers
- Editorials and position papers expressing an opinion about research
- Work in progress destined for peer-reviewed publication
- Blog post-sized chunks of work that are of interest to the community but might be lost in or delayed by the traditional publishing process
- Announcements about relevant workshops and conferences
We review the proceedings of relevant conferences such as CHI, Collective Intelligence, CSCW, HCOMP, GROUP, UIST, WSDM, and other venues; authors of relevant papers are invited to post.
We also welcome unsolicited posts. If you’d like to submit one, please see our submission instructions.
Who should I blame?
- Michael Bernstein, Stanford University
- Lydia Chilton, University of Washington
- Sanjay Kairam, Stanford University
- Anand Kulkarni, UC Berkeley
- Reid Priedhorsky, Los Alamos National Laboratory
- Alex Quinn, University of Maryland
- Jeff Rzesotarski, Carnegie Mellon University
- Haoqi Zhang, Northwestern University
If you’d like to join, please e-mail us.
- Ed H. Chi, Google Research
- Bjoern Hartmann, UC Berkeley
- Niki Kittur, Carnegie Mellon University
- Rob Miller, MIT