Carnegie Mellon University

Tracking Political Sentiments Using Machine Learning

Course Number: 84-740

Online social media provides a rich source of detailed data reflecting the evolution of political sentiments over time, and in response to various news events. This seminar course studies a diverse set of recent papers in the intersection of machine learning, natural language processing and political science with an aim to pose non-trivial research questions concerning US politics and devise ML and NLP framework for answering them. A key component of the course is a semester-long research project with a view toward a peer-reviewed publication. The course provides a large text data set relevant to US politics and the goal is for each student to formulate, explore, and understand a focused research question through the lens of this data set. By the end of the course, apart from acquiring hands-on experience in realizing the synergy between large scale data, creative research questions and effective NLP solutions, we all hope to have an improved understanding of why we are in what we are in. The course will provide some useful data sets and a list of potential project ideas for its primary focus -- the semester-long project. Students will work in small teams (one to two members) on course projects. The course engineer will provide useful scripts and code to efficiently process data. The course requires familiarity with machine learning at a level of being able to complete a substantial project. Students without the necessary prerequisites should contact the instructor for special permission.

Academic Year: 2022-2023
Semester(s): Fall
Required/Elective: Elective
Units: 12
Location(s): Pittsburgh

Fall 2022
Monday and Wednesday
3:05-4:25 PM

Elective course for the following IPS degree:
Master of Information Technology Strategy