Publication: KUNLPLab: sentiment analysis on twitter data
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This paper presents the system submitted by KUNLPLab for SemEval-2014 Task9 - Subtask B: Message Polarity on Twitter data. Lexicon features and bag-of-words features are mainly used to represent the datasets. We trained a logistic regression classifier and got an accuracy of 6% increase from the baseline feature representation. The effect of pre-processing on the classifier’s accuracy is also discussed in this work. © 8th International Workshop on Semantic Evaluation, SemEval 2014 - co-located with the 25th International Conference on Computational Linguistics, COLING 2014, Proceedings.
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Association for Computational Linguistics (ACL)
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Engineering, Computer Science, Artificial intelligence
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8th International Workshop on Semantic Evaluation, SemEval 2014 - co-located with the 25th International Conference on Computational Linguistics, COLING 2014, Proceedings