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Graph Learning for Fake Review Detection [PDF]

Frontiers in Artificial Intelligence, 2022
Fake reviews have become prevalent on various social networks such as e-commerce and social media platforms. As fake reviews cause a heavily negative influence on the public, timely detection and response are of great significance. To this end, effective
Shuo Yu, Jing Ren, Shihao Li, Mehdi Naseriparsa, Feng Xia   +4 more
doaj   +5 more sources

Confounds and overestimations in fake review detection: Experimentally controlling for product-ownership and data-origin. [PDF]

PLoS ONE, 2022
The popularity of online shopping is steadily increasing. At the same time, fake product reviews are published widely and have the potential to affect consumer purchasing behavior.
Felix Soldner, Bennett Kleinberg, Shane D Johnson   +2 more
doaj   +3 more sources

High performance fake review detection using pretrained DeBERTa optimized with Monarch Butterfly paradigm. [PDF]

Sci Rep
In this era of internet, e-commerce has grown tremendously and the customers are increasingly relying on reviews for product information. As these reviews influence the purchasing ability of the future customer, it can give a positive or negative impact ...
Geetha S, Elakiya E, Kanmani RS, Das MK.
europepmc   +2 more sources

Fake Reviews Detection: A Survey [PDF]

IEEE Access, 2021
In e-commerce, user reviews can play a significant role in determining the revenue of an organisation. Online users rely on reviews before making decisions about any product and service.
Rami Mohawesh, Shuxiang Xu, Son N. Tran, Robert Ollington, Matthew Springer, Yaser Jararweh, Sumbal Maqsood   +6 more
doaj   +2 more sources

A systematic literature review about the consumers’ side of fake review detection – Which cues do consumers use to determine the veracity of online user reviews?

Computers in Human Behavior Reports, 2023
Background: Consumers rely heavily on online user reviews when shopping online and cybercriminals produce fake reviews to manipulate consumer opinion.
Michelle Walther, Timo Jakobi, Steven James Watson, Gunnar Stevens   +3 more
doaj   +2 more sources

Fake Review Detection

International Journal for Research in Applied Science and Engineering Technology
The Fake Review Detection System: A Review SHIKHAR RAJ GUPTA, RESHU SINGH Computer Science and Engineering, Babu Banarasi Das Northern Indian Institute of Technology Lucknow, India ABSTRACT Fake Reviews: In the age of digital commerce, user-generated reviews significantly influence consumer decisions and business reputations.
Shikhar Raj Gupta
openaire   +2 more sources

An explainable ensemble of multi-view deep learning model for fake review detection

Journal of King Saud University: Computer and Information Sciences, 2023
Online reviews significantly impact consumers who are purchasing or seeking services via the Internet. Businesses and review platforms need to manage these online reviews to avoid misleading customers through fake ones.
Rami Mohawesh, Shuxiang Xu, Matthew Springer, Yaser Jararweh, Muna Al-Hawawreh, Sumbal Maqsood   +5 more
doaj   +2 more sources

Fake Review Detection System

International Journal for Research in Applied Science and Engineering Technology
In today's business landscape, online reviews play a crucial role in shaping commerce. A large portion of purchase decisions for online products is driven by customer feedback. Consequently, some individuals or groups try to manipulate product reviews to their advantage.
Prof. Suchitra Deokute
openaire   +2 more sources

Fake review detection using transformer-based enhanced LSTM and RoBERTa

International Journal of Cognitive Computing in Engineering
Internet reviews significantly influence consumer purchase decisions across all types of goods and services. However, fake reviews can mislead both customers and businesses. Many machine learning (ML) techniques have been proposed to detect fake reviews,
Rami Mohawesh, Haythem Bany Salameh, Yaser Jararweh, Mohannad Alkhalaileh, Sumbal Maqsood   +4 more
doaj   +2 more sources

Cross-Domain Fake Review Detection via Orthogonal Counterfactual Representations

IEEE Access
The popularity of online review-based purchases has led many businesses to generate fake reviews. Manual detection of these fakes is a challenging task. Moreover, existing research focuses primarily on single domain.
Richa Gupta, Vinita Jindal, Indu Kashyap
doaj   +2 more sources