2016
COLING
COLING 2016
Targeted Sentiment to Understand Student Comments
Abstract
AbstractWe address the task of targeted sentiment as a means of understanding the sentiment that students hold toward courses and instructors, as expressed by students in their comments. We introduce a new dataset consisting of student comments annotated for targeted sentiment and describe a system that can both identify the courses and instructors mentioned in student comments, as well as label the students’ sentiment toward those entities. Through several comparative evaluations, we show that our system outperforms previous work on a similar task.
🌉
Interdisciplinary Bridge
— Artificial Intelligence and Machine Learning
🧭
Keyword Pioneer
— targeted sentiment
🐣
Hot Topic Early Bird
— opinion mining
🐝
Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio