A fake review identification framework considering the suspicion degree of reviews with time burst characteristics

作者：

Highlights：

• Time burst characteristic is studied by 3 aspects in fake review identification.

• A suspicion degree method of fake reviews is proposed from (1) by LOF algorithm.

• A fake review identification framework is given including the suspicion degree.

• The case study shows that the proposed method outperforms the existed methods.

摘要

•Time burst characteristic is studied by 3 aspects in fake review identification.•A suspicion degree method of fake reviews is proposed from (1) by LOF algorithm.•A fake review identification framework is given including the suspicion degree.•The case study shows that the proposed method outperforms the existed methods.

论文关键词：Fake review,Time series,Machine learning,Data and text mining,Doc2vec

论文评审过程：Received 8 September 2020, Revised 12 July 2021, Accepted 6 November 2021, Available online 12 November 2021, Version of Record 25 November 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.116207