A Proposed Solution for Identifying Online Fake Reviews in the Research Process

Abstract

This chapter aims to present the issue of manipulation of online reviews, behind which there is always an interest, whether it is about increasing sales, promoting a product, degrading the image of a competing brand or product. Such reviews can influence the purchase decision or the sales of a company. Combining users text with their behavior has yielded the best results in identifying fake reviews, and this remains probably the most effective method to date. The chapter proposes, as a novelty factor, a methodological solution before analyzing reviews through specialized software (e.g., SmartMunk, Revuze, Aspectiva, SentiGeek, etc.), a filter for identifying fake reviews by introducing them into a fake review application called Fakespot. Moreover, the idea that these false reviews can influence the purchase decision of customers in any field is emphasized, so it is very important that large companies develop programs or systems that detect them.