SI 301 - Models of Social Information Processing
Section: 001
Term: WN 2010
Subject: Information (SI)
Department: School of Information
May not be repeated for credit.
Primary Instructor:

This course focuses on how social groups form, interact, and change. We look at the technical structures of social networks and explore how individual actions are combined to produce collective effects. The techniques learned in this course can be applied to understanding friend systems like Facebook, recommender systems such as Digg, auction systems such as Ebay, and information webs used by search engines such as Google. This course introduces two conceptual models, networks and games, for how information flows and is used in multi-person settings. Network or graph representations describe the structure of connections among people and documents. They permit mathematical analysis and meaningful visualizations that highlight different roles played by different people or documents, as well as features of the collection as whole. Game representations describe, in situations of interdependence, the actions available to different people and how each person’s outcomes are contingent on the choices of other people. It permits analysis of stable sets of choices by all the people (equilibriums). It also provides a framework for analysis of the likely effects of alternative designs for markets and information elicitation mechanisms, based on their abstract game representations. Assignments in the course include problem sets exploring the mechanics of the models and essays applying them to current applications in social computing.

Prerequisite: familiarity with Python is helpful.

SI 301 - Models of Social Information Processing
Schedule Listing
001 (LEC)
W 8:30AM - 11:30AM
NOTE: Data maintained by department in Wolverine Access. If no textbooks are listed below, check with the department.

Coursepack Location:
Dollar Bill Copying
This course will use an as-yet-unpublished book which will be available from Dollar Bill Copying.
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