Meta-Classifiers Easily Improve Commercial Sentiment Detection Tools
2014-05-01LREC 2014Unverified0· sign in to hype
Mark Cieliebak, Oliver D{\"u}rr, Fatih Uzdilli
Unverified — Be the first to reproduce this paper.
ReproduceAbstract
In this paper, we analyze the quality of several commercial tools for sentiment detection. All tools are tested on nearly 30,000 short texts from various sources, such as tweets, news, reviews etc. The best commercial tools have average accuracy of 60\%. We then apply machine learning techniques (Random Forests) to combine all tools, and show that this results in a meta-classifier that improves the overall performance significantly.