Text Mining and Sentiment Analysis
A.Y. 2025/2026
Learning objectives
Understand the state of the art on text mining and sentiment analysis. Design and develop methods for text classification and topic modeling. Design and develop methods for sentiment classification and polarity detection. Understand the differences between sentiment analysis and emotion detection. Design and develop methods for emotion detection in text.
Expected learning outcomes
At the end of the course the student will be able to address a specific problem in the area of text mining and sentiment analysis. In particular student will know he main notions needed to understand text processing, foundations of natural language processing, text classification, and topic modeling. Moreover students will deal with sentiment analysis in the context of opinion mining and rule-based models and machine learning models for text.
Lesson period: Second four month period
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Lesson period
Second four month period
Course syllabus
The syllabus is shared with the following courses:
- [F94-166](https://www.unimi.it/en/ugov/of/af2026000f94-166)
- [F94-166](https://www.unimi.it/en/ugov/of/af2026000f94-166)
INF/01 - INFORMATICS - University credits: 6
Lessons: 40 hours