Email thread sentiment sequence identification using PLSA clustering algorithm

作者：

Highlights：

• SentiWordNet lexicon is used for generating sentiment features of email data.

• Probabilistic Latent Semantic Analysis algorithm is used for clustering.

• The sentiment sequence of thread and thread size are identified.

• Evaluated the proposed model using accuracy, precision, recall and F-measure.

摘要

•SentiWordNet lexicon is used for generating sentiment features of email data.•Probabilistic Latent Semantic Analysis algorithm is used for clustering.•The sentiment sequence of thread and thread size are identified.•Evaluated the proposed model using accuracy, precision, recall and F-measure.

论文关键词：Sentiment email clusters,Probabilistic latent semantic analysis,Topic modeling,SWN lexicon,Sentiment sequence of threads

论文评审过程：Received 18 March 2020, Revised 7 December 2021, Accepted 26 December 2021, Available online 3 January 2022, Version of Record 6 January 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.116475