Results 1 to 10 of about 284,665 (285)
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 +4 more
doaj +4 more sources
Fake review identification and utility evaluation model using machine learning [PDF]
Frontiers in Artificial Intelligence, 2023 Due to the structural growth of e-commerce platforms, the frequency of exchange of opinions and the number of online reviews of platform participants related to products are increasing.
Wonil Choi +5 more
doaj +2 more sources
Determinants of multimodal fake review generation in China’s E-commerce platforms [PDF]
Scientific ReportsThis paper develops a theoretical model of determinants influencing multimodal fake review generation using the theories of signaling, actor-network, motivation, and human–environment interaction hypothesis.
Chunnian Liu, Xutao He, Lan Yi
doaj +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 +6 more
doaj +2 more sources
Authentic and Fake Reviews Recognition on E-Commerce Websites through Sentiment Analysis and Machine Learning Techniques [PDF]
International Journal of Web Research, 2023 The proliferation of e-commerce has led to an overwhelming volume of customer reviews, posing challenges for consumers who seek reliable product evaluations and for businesses concerned with the integrity of their online reputation.
Kian Nimgaz Naghsh +1 more
doaj +1 more source
The Economic Journal, 2020 Abstract We propose a model of product reviews in which some are genuine and some are fake in order to shed light on the value of information provided on platforms like TripAdvisor, Yelp, etc. In every period, a review is posted which is either genuine or fake.
Glazer, Jacob +2 more
openaire +1 more source
IEEE Access, 2021 With the widespread of fake online reviews, the detection of fake reviews has become a hot research issue. Despite the efforts of existing studies on fake review detection, the issues of imbalanced data and feature pruning still lack sufficient attention.
Jianrong Yao, Yuan Zheng, Hui Jiang
doaj +1 more source
Trust Model for Online Reviews of Tourism Services and Evaluation of Destinations
Administrative Sciences, 2021 Obtaining information about destinations and services they provide is ever more based on user-generated content (UGC), which includes reviews of tourism services as well as evaluation of attractions and destinations by visitors. The growing importance of
Josef Zelenka +2 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 +5 more
doaj +1 more source
Machine learning-based Fake reviews detection with amalgamated features extraction method
Sukkur IBA Journal of Emerging Technologies, 2023 Product fake reviews are increasing as the trend is changing toward online sales and purchases. Fake review detection is critical and challenging for both researchers and online retailers.
Muhammad Bux Alvi +4 more
doaj +1 more source