Paper: NTNU: Domain Semi-Independent Short Message Sentiment Classification

ACL ID S13-2071
Title NTNU: Domain Semi-Independent Short Message Sentiment Classification
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2013
Authors

The paper describes experiments using grid searches over various combinations of ma- chine learning algorithms, features and pre- processing strategies in order to produce the optimal systems for sentiment classification of microblog messages. The approach is fairly domain independent, as demonstrated by the systems achieving quite competitive results when applied to short text message data, i.e., input they were not originally trained on.