Evaluation of AI Techniques for Detecting Deceptive Reviews in Cyberspace: A Study of Pre- and Post-COVID-19 Trends
2nd International Conference on Electronics and Renewable Systems, ICEARS 2023
; : 961-967, 2023.
Article
in English
| Scopus | ID: covidwho-2303023
ABSTRACT
With cyberspace's continuous evolution, online reviews play a crucial role in determining business success in various sectors, ranging from restaurants and hotels to e-commerce applications. Typically, a favorable review for a specific product draws in more consumers and results in a significant boost in sales. Unfortunately, a few businesses are using deceptive methods to improve their online reputation by using fake reviews of competitors. As a result, detecting fake reviews has become a difficult and ever-changing research field. Verbal characteristics extracted from review text, as well as nonverbal features such as the reviewer's engagement metrics, the IP address of the device, and so on, play an important role in detecting fake reviews. This article examines and compares various machine learning techniques for detecting deceptive reviews on various online platforms such as e-commerce websites such as Amazon and online review websites such as Yelp, among others. © 2023 IEEE.
Amazon Reviews; COVID-19; Data Resampling; Decision Tree (DT-J48); E-commerce; Ensemble model; Fake Review; Feature pruning; Logistic Regression (LR); Naïve Bayes (NB); Parameter optimization; Sentiment Analysis; Support Vector Machine (SVM); Yelp; Adaptive boosting; Decision trees; Electronic commerce; Fake detection; Feature extraction; Learning systems; Logistic regression; Websites; Amazon review; Decision trees (DTs); Ensemble models; Logistics regressions; Naive baye; Naive bayes; Resampling; Support vector machine; Support vectors machine; Support vector machines
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Experimental Studies
Topics:
Long Covid
Language:
English
Journal:
2nd International Conference on Electronics and Renewable Systems, ICEARS 2023
Year:
2023
Document Type:
Article
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