LIPN-UAM at EmoInt-2017:Combination of Lexicon-based features and Sentence-level Vector Representations for Emotion Intensity Determination
This paper presents the combined LIPN-UAM participation in the WASSA 2017 Shared Task on Emotion Intensity. In particular, the paper provides some highlights on the Tweetaneuse system that was presented to the shared task. We combined lexicon-based features with sentence-level vector representations to implement a random forest regressor.
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Emotion RecognitionSentenceSentiment AnalysisWord EmbeddingsSimilar Papers 제목 키워드 기반
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