Sentiment Analysis of User-generated Content

The proliferation of user generated content on the Web is driving a new wave of work determining user sentiment from web texts such as message boards, blogs, tweets, and Facebook status updates. Both researchers and practitioners are developing and applying new methods to determine how users feel about everything: products and politicians, friends and family, scientific articles and celebrities. This short course will cover the state of the art in this rapidly growing area, including recent advances that combine information extraction with sentiment analysis to improve accuracy in assessing sentiment about specific entities, and use of NLP to understand people’s personality and health behaviors. Real world applications of sentiment analysis will be presented.

Instructor

• Lyle Ungar

Prerequisites:

• none
• if you want to study anything, take an introductory machine learning course such as Andrew Ng’s ML coursera one. You might skip straight to the lecture on regularization

Course Lectures

Course Readings

• reading are optional; read them afterwards to learn the details.