Social media provides a massive amount of valuable information and shows us how language is actually used by lots of people. This course will give an overview of prominent research findings on language use in social media. The course will also cover several machine learning algorithms and the core natural language processing techniques for obtaining and processing Twitter data.
- Wei Xu is an assistant professor in the Department of Computer Science and Engineering at the Ohio State University. Her research interests lie at the intersection of machine learning, natural language processing, and social media. She holds a PhD in Computer Science from New York University. Prior to joining OSU, she was a postdoc at the University of Pennsylvania. She is organizing the ACL/COLING Workshop on Noisy User-generated Text, serving as a workshop co-chair for ACL 2017, an area chair for EMNLP 2016 and the publicity chair for NAACL 2016.
- Fall 2016, CSE 5539-0010 The Ohio State University
Cockins Hall Room 218 | Wednesday 2:20PM – 4:10PM
dual-listed undergraduate and graduate course
- In order to succeed in this course, you should know basic probability and statistics, such as the chain rule of probability and Bayes’ rule. On the programming side, all projects will be in Python. You should understand basic computer science concepts (like recursion), basic data structures (trees, graphs), and basic algorithms (search, sorting, etc).
- Various academic papers
- This is a project-based course (total 100 points). Instead of exams, you will do three hands-on programming assignments. Everyone can have 3 free late days without penalty. After you have used your free late days, you will lose 20% per day that your assignment is submitted late.
- Homework #1 (20 points/individual)
- Homework #2 (30 points/individual)
- Homework #3 (30 points/group) or a research project (optional)
- In-class Presentation (20 points/group)
- Quizzes (bonus 10 points)
- Participation in class and/or on the Piazza discussion board (bonus 10 points)
- Summer 2016, The North American Summer School on Logic, Language, and Information (NASSLLI)
Teaching evaluation was 5.72 out of 6 at NASSLLI; average across all instructors was 5.23.
Summer 2015, University of Pennsylvania (where this course was first designed and taught)