Short text opinion detection using ensemble of classifiers and semantic indexing

作者：

Highlights：

• An ensemble system to perform opinion detection in short text messages is proposed.

• The model combines the state-of-the-art classification methods and NLP techniques.

• The proposed ensemble can improve performance of the most text categorization tasks.

• Experimental results on nine real English public datasets are reported.

• The proposed method is statistically superior to the compared approaches.

摘要

•An ensemble system to perform opinion detection in short text messages is proposed.•The model combines the state-of-the-art classification methods and NLP techniques.•The proposed ensemble can improve performance of the most text categorization tasks.•Experimental results on nine real English public datasets are reported.•The proposed method is statistically superior to the compared approaches.

论文关键词：Sentiment analysis,Text normalization,Semantic indexing,Classification,Machine learning

论文评审过程：Received 15 March 2016, Revised 2 June 2016, Accepted 12 June 2016, Available online 16 June 2016, Version of Record 23 June 2016.

论文官网地址：https://doi.org/10.1016/j.eswa.2016.06.025