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- W222104007 abstract "We study sentiment analysis beyond the typical granularity of polarity and instead use Plutchik's wheel of emotions model. We introduce RBEM-Emo as an extension to the Rule-Based Emission Model algorithm to deduce such emotions from human-written messages. We evaluate our approach on two different datasets and compare its performance with the current state-of-the-art techniques for emotion detection, including a recursive auto-encoder. The results of the experimental study suggest that RBEM-Emo is a promising approach advancing the current state-of-the-art in emotion detection." @default.
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- W222104007 date "2014-12-15" @default.
- W222104007 modified "2023-09-27" @default.
- W222104007 title "Rule-based Emotion Detection on Social Media: Putting Tweets on Plutchik's Wheel" @default.
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