Paper: Senti.ue: Tweet Overall Sentiment Classification Approach for SemEval-2014 Task 9

ACL ID S14-2095
Title Senti.ue: Tweet Overall Sentiment Classification Approach for SemEval-2014 Task 9
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2014
Authors

This document describes the senti.ue system and how it was used for partici- pation in SemEval-2014 Task 9 challenge. Our system is an evolution of our prior work, also used in last year?s edition of Sentiment Analysis in Twitter. This sys- tem maintains a supervised machine learn- ing approach to classify the tweet overall sentiment, but with a change in the used features and the algorithm. We use a re- stricted set of 47 features in subtask B and 31 features in subtask A. In the constrained mode, and for the five data sources, senti.ue achieved a score between 78,72 and 84,05 in subtask A, and a score between 55,31 and 71,39 in sub- task B. For the unconstrained mode, our score was slightly below, except for one case in subtask A.