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ECNU: Multi level Sentiment Analysis on Twitter Using Traditional Linguistic Features and Word Embedding Features

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Figure

Table 3: Results of subtask A and B using traditional fea-tures, word embedding features and their combination interms of Fma c r o on training data.
Table 2: Results of feature selection experiments for subtask A, B and C in terms of Fma c r o on the training data.The numbers in the brackets are the performance increments compared with the previous results
Table 7: Performances of our systems and the top-rankedsystems for subtask E. The numbers in the brackets arethe official ranking.

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