Results 1 to 10 of about 37,947 (280)

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

Graph Learning for Fake Review Detection

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   +3 more sources

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

Scientific Reports
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 ...
S. Geetha, E. Elakiya, R. Sujithra Kanmani, Manas Kamal Das   +3 more
doaj   +2 more sources

Multi-Modal Anomaly Detection in Review Texts with Sensor-Derived Metadata Using Instruction-Tuned Transformers [PDF]

Sensors
Fake review detection is critical for maintaining trust and ensuring decision reliability across digital marketplaces and IoT-enabled ecosystems. This study presents a zero-shot framework for multi-modal anomaly detection in user reviews, integrating ...
Khaled M. Alhawiti
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   +1 more source

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   +1 more source

Fake Online Reviews: A Unified Detection Model Using Deception Theories

IEEE Access, 2022
Online reviews influence consumers’ purchasing decisions. However, identifying fake online reviews automatically remains a complex problem, and current detection approaches are inefficient in preventing the spread of fake reviews.
Mujahed Abdulqader, Abdallah Namoun, Yazed Alsaawy   +2 more
doaj   +1 more source

Detecting Fake Reviews in Google Maps—A Case Study

Applied Sciences, 2023
Many customers rely on online reviews to make an informed decision about purchasing products and services. Unfortunately, fake reviews, which can mislead customers, are increasingly common.
Paweł Gryka, Artur Janicki
doaj   +1 more source

Fake Review Detection System: A Review

International Journal of Scientific Research in Science and Technology, 2023
Fake reviews, often referred to as deceptive or dishonest reviews, have become a significant concern for both businesses and consumers (Feng et al., 2016). These reviews are deliberately crafted to mislead or manipulate the opinions of others and can be driven by various motives, such as financial gain, competition, or personal grudges (Liu et al ...
null Dr. Pankaj Kumar, null Alok Verma, null Anurag Srivastava, null Ayushi Pal   +3 more
openaire   +1 more source

Do Reviewers’ Words and Behaviors Help Detect Fake Online Reviews and Spammers? Evidence From a Hierarchical Model

IEEE Access, 2022
Although numerous studies have investigated spam detection and spammer detection on online platforms, they have ignored the fact that reviews written by the same reviewer may be correlated because each reviewer has their own distinct style.
Thi-Kim-Hien Le, Yi-Zhen Li, Sheng-Tun Li   +2 more
doaj   +1 more source