The Fake Review Effect On E-commerce :SKL-Based Fake Review Detection

Dr.S.Selvakani , K.Vasumathi , J V Hemakumar

Fake reviews, k-nearest neighbor (KNN), Machine learning, Natural language processing, Sentiment analysis, Support vector machine (SVM)

The significance of reviews on any e-commerce website cannot be overstated, as they often serve as the basis for a potential buyer's purchasing decision. Reviews enable buyers to assess the authenticity and quality of a product based on the feedback provided by other customers. However, some sellers take advantage of reviews by publishing reviews that either promote or discredit a product. These reviews, which do not represent the genuine opinion of an individual, are referred to as fake reviews. The existence of such fake reviews can lead to inaccurate judgments by buyers, which can also damage the platform's credibility. As a result, detecting fake reviews is critical. This paper proposes a method for identifying fake reviews on the platform using a logistic regression model that considers review-specific characteristics and achieves an overall accuracy of 82%. Additionally, our research demonstrates the importance of the "verified purchase" feature in identifying fake reviews.

Published Paper   E-Certificate

"The Fake Review Effect On E-commerce :SKL-Based Fake Review Detection", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 3, page no.d436-d440, March-2023, Available :https://ijnrd.org/papers/IJNRD2303357.pdf

Volume 8 Issue 3, March-2023

Pages : d436-d440

Paper Reg. ID: IJNRD_189278

Published Paper Id: IJNRD2303357

Downloads: 000118839

Research Area: Science

Country: Arakkonam, Ranipet, Tamilnadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2303357

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2303357

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition