A case study of Spanish text transformations for twitter sentiment analysis

作者：

Highlights：

• A review of popular techniques to model short texts written in an informal style.

• An analysis of configurations that produce the top-k sentiment classifiers.

• The analysis is oriented to the performance in both accuracy and computing time.

• A simple method to create fast and accurate sentiment analysis systems.

摘要

•A review of popular techniques to model short texts written in an informal style.•An analysis of configurations that produce the top-k sentiment classifiers.•The analysis is oriented to the performance in both accuracy and computing time.•A simple method to create fast and accurate sentiment analysis systems.

论文关键词：Sentiment analysis,Error-robust text representations,Opinion mining

论文评审过程：Received 1 June 2016, Revised 11 March 2017, Accepted 30 March 2017, Available online 31 March 2017, Version of Record 7 April 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.03.071