Multi-class sentiment classification: The experimental comparisons of feature selection and machine learning algorithms

作者：

Highlights：

• A framework for multi-class sentiment classification is proposed.

• A total of 3600 comparative experiments are conducted.

• Performances of different feature selection/machine learning algorithms are compared.

• The results are valuable for further studies on multi-class sentiment classification.

摘要

•A framework for multi-class sentiment classification is proposed.•A total of 3600 comparative experiments are conducted.•Performances of different feature selection/machine learning algorithms are compared.•The results are valuable for further studies on multi-class sentiment classification.

论文关键词：Multi-class sentiment classification,Experimental comparison,Feature selection algorithms,Machine learning algorithms

论文评审过程：Received 6 October 2016, Revised 20 March 2017, Accepted 21 March 2017, Available online 21 March 2017, Version of Record 27 March 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.03.042