Paper: NRC-Canada-2014: Recent Improvements in the Sentiment Analysis of Tweets

ACL ID S14-2077
Title NRC-Canada-2014: Recent Improvements in the Sentiment Analysis of Tweets
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2014
Authors

This paper describes state-of-the-art statis- tical systems for automatic sentiment anal- ysis of tweets. In a Semeval-2014 shared task (Task 9), our submissions obtained highest scores in the term-level sentiment classification subtask on both the 2013 and 2014 tweets test sets. In the message-level sentiment classification task, our submis- sions obtained highest scores on the Live- Journal blog posts test set, sarcastic tweets test set, and the 2013 SMS test set. These systems build on our SemEval-2013 senti- ment analysis systems (Mohammad et al., 2013) which ranked first in both the term- and message-level subtasks in 2013. Key improvements over the 2013 systems are in the handling of negation. We create separate tweet-specific sentiment lexicons for terms in affirmative contexts and ...