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Potential and Limitations of Commercial Sentiment Detection Tools
2013
International Conference of the Italian Association for Artificial Intelligence
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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. In addition to the quality analysis (measured by various metrics), we also investigate the effect of increasing text length on the performance. Finally, we show that combining all tools using machine learning techniques increases the overall performance significantly.
dblp:conf/aiia/CieliebakDU13
fatcat:xwulf4va4rfkpgynfkjzjmwbaa