POS-RS: A Random Subspace method for sentiment classification based on part-of-speech analysis

作者：

Highlights：

• The rise of social media has fueled interest in sentiment classification.

• POS-RS is proposed for sentiment analysis based on part-of-speech analysis.

• Ten public datasets were investigated to verify the effectiveness of POS-RS.

• Experimental results reveal POS-RS can be used as a viable method.

摘要

•The rise of social media has fueled interest in sentiment classification.•POS-RS is proposed for sentiment analysis based on part-of-speech analysis.•Ten public datasets were investigated to verify the effectiveness of POS-RS.•Experimental results reveal POS-RS can be used as a viable method.

论文关键词：Sentiment classification,Random Subspace,Part of speech,Ensemble learning

论文评审过程：Received 15 August 2013, Revised 24 September 2014, Accepted 29 September 2014, Available online 24 October 2014, Version of Record 6 June 2015.

论文官网地址：https://doi.org/10.1016/j.ipm.2014.09.004