Research on false review detection Methods: A state-of-the-art review

Fake reviews are popular today where product reviewers write the reviews without experiencing or pur-chasing the product on e-commerce and restaurant portals. Currently, the false review recognition method uses the systematic review process to extract, summarise, and classify the meaningful content of the research, compare and analyse the representation power of various false attributes, and the recog-nition method's performance. Feature design and recognition method design are the key steps for false review text recognition. The procurement of a large-scale labelled review dataset is difficult in recent research. They were only identifying fake review texts used as the core of the discussion. The article pre-sents an assessment of fake reviews detection in different domains (hotels and e-commerce). In this arti-cle, we have also identified the relation between fake reviewers and groups of fake reviewers. We have analysed and pointed out the existing research problems in data acquisition, false feature design, and recognition method design to suggest future research on false review detection. (c) 2021 The Authors. Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Automated summary

The article discusses methods for identifying fake reviews and related issues. The main difficulty at present is obtaining a large-scale tagged review dataset.