Mengxiao Jiang

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2017

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ECNU at SemEval-2017 Task 5: An Ensemble of Regression Algorithms with Effective Features for Fine-Grained Sentiment Analysis in Financial Domain
Mengxiao Jiang | Man Lan | Yuanbin Wu
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)

This paper describes our systems submitted to the Fine-Grained Sentiment Analysis on Financial Microblogs and News task (i.e., Task 5) in SemEval-2017. This task includes two subtasks in microblogs and news headline domain respectively. To settle this problem, we extract four types of effective features, including linguistic features, sentiment lexicon features, domain-specific features and word embedding features. Then we employ these features to construct models by using ensemble regression algorithms. Our submissions rank 1st and rank 5th in subtask 1 and subtask 2 respectively.

2016

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ECNU at SemEval-2016 Task 5: Extracting Effective Features from Relevant Fragments in Sentence for Aspect-Based Sentiment Analysis in Reviews
Mengxiao Jiang | Zhihua Zhang | Man Lan
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)

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