- About
- Courses
- Research
- Computational Social Science
- Critical Data Studies
- Data Science
- Economics and Information
- Education Technology
- Ethics, Law and Policy
- Human-Computer Interaction
- Human-Robot Interaction
- Incentives and Computation
- Infrastructure Studies
- Interface Design and Ubiquitous Computing
- Natural Language Processing
- Network Science
- Social Computing and Computer-supported Cooperative Work
- Technology and Equity
- People
- Career
- Undergraduate
- Info Sci Majors
- BA - Information Science (College of Arts & Sciences)
- BS - Information Science (CALS)
- BS - Information Science, Systems, and Technology
- MPS Early Credit Option
- Independent Research
- CPT Procedures
- Student Associations
- Undergraduate Minor in Info Sci
- Our Students and Alumni
- Graduation Info
- Contact Us
- Info Sci Majors
- Masters
- PHD
- Prospective PhD Students
- Admissions
- Degree Requirements and Curriculum
- Grad Student Orgs
- For Current PhDs
- Diversity and Inclusion
- Our Students and Alumni
- Graduation Info
- Program Contacts and Student Advising
Related Research Areas
Moon Duchin is new to Cornell, based in the Math Department and the Brooks School of Public Policy. She runs a lab that applies tools of data science to democratic mechanisms, especially redistricting and voting rules.
Talk: Communities of interest
Abstract: In the world of political redistricting, many states have a rule on the books that the lines should take "communities of interest" into account. But what in the world does this mean? Both the problem of identifying salient communities and the problem of what it means to "respect" or "reflect" them are wildly hard and interesting challenges that combine geography, sociology, natural language processing, and theories of political representation. I'll set the stage theoretically and then tell some tales from the trenches about what it looks like to take this districting principle seriously.