Paper: Coooolll: A Deep Learning System for Twitter Sentiment Classification

ACL ID S14-2033
Title Coooolll: A Deep Learning System for Twitter Sentiment Classification
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2014
Authors

In this paper, we develop a deep learn- ing system for message-level Twitter sen- timent classification. Among the 45 sub- mitted systems including the SemEval 2013 participants, our system (Coooolll) is ranked 2nd on the Twitter2014 test set of SemEval 2014 Task 9. Coooolll is built in a supervised learning framework by concatenating the sentiment-specific word embedding (SSWE) features with the state-of-the-art hand-crafted features. We develop a neural network with hybrid loss function 1 to learn SSWE, which en- codes the sentiment information of tweets in the continuous representation of words. To obtain large-scale training corpora, we train SSWE from 10M tweets collected by positive and negative emoticons, without any manual annotation. Our system can be easily re-implemented with th...