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MS&E231

Social Algorithms

Management Science and Engineering ENGR - School of Engineering

Course Description

Learning algorithms play increasingly central roles within modern complex social systems. In this course, we examine the design and behavior of algorithms in such contexts, including search algorithms, content recommendation systems, social recommendation algorithms, feed ranking algorithms, content moderation algorithms, and more. The course has a split focus on the technical design of such algorithms, as well the literature on theoretical and empirical evaluations in the presence of network effects, strategic behavior, and algorithmic confounding. Prerequisites: training in applied statistics at the level of MS&E 125 or above, including experience coding in Python.

Cross Listed Courses

Grading Basis

ROP - Letter or Credit/No Credit

Min

3

Max

3

Course Repeatable for Degree Credit?

No

Course Component

Discussion

Enrollment Optional?

Yes

Course Component

Lecture

Enrollment Optional?

No

Programs

MS&E231 is a completion requirement for: