Sarcasm is a sophisticated form of act where one says or writes the opposite of what they mean. Sarcasm is a common issue in sentiment analysis and detecting it is a challenge. While models for sarcasm detection have been proposed for general purposes (e.g. Twitter data, Amazon reviews), there is no research addressing this issue in an educational context, despite the increased use of social media in education. In this paper we experiment with several machine learning techniques, features and preprocessing levels to identify sarcasm from students' feedback collected via Twitter.
|Name||Lecture Notes in Computer Science|
|Conference||10th European Conference on Technology Enhanced Learning, EC-TEL|
|Period||14/09/15 → …|
The final publication is available at link.springer.com