Results 231 to 240 of about 37,947 (280)

When Infodemic Meets Epidemic: Systematic Literature Review.

JMIR Public Health Surveill
Asaad C, Khaouja I, Ghogho M, Baïna K.
europepmc   +1 more source

Political affiliation or need for cognition? It depends on the post: Comparing key factors related to detecting health disinformation in the U.S. [PDF]

PLoS One
George JF.
europepmc   +1 more source

Identifying Disinformation on the Extended Impacts of COVID-19: Methodological Investigation Using a Fuzzy Ranking Ensemble of Natural Language Processing Models.

J Med Internet Res
Chen JA, Chung WC, Hung CL, Wu CY.
europepmc   +1 more source

Health Misinformation Detection: Approaches, Challenges and Opportunities. [PDF]

Inquiry
Feng X, Luo J, Yang Y, El Baz D, Shi L.
europepmc   +1 more source

Ensemble learning approach for distinguishing human and computer-generated Arabic reviews. [PDF]

PeerJ Comput Sci
Alhayan F, Himdi H.
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False authorship: an explorative case study around an AI-generated article published under my name. [PDF]

Res Integr Peer Rev
Spinellis D.
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Fake Customer Review Detection System

International Journal of Innovative Research in Engineering, 2023
Online purchasing is rising bit by bit since each service or product is easily accessible. Sellers are obtaining more reaction to one’s corporation factors. Several people generally frustrated kinds of persons misdirect others by sharing false comments to encourage or damage the image of any specific goods or services according to wish. Such people are
Abhishek Kumar Roy, Devsharan Singh, Imran Raeeni, Izmamul Ansari   +3 more
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Towards Amazon Fake Reviewers Detection

Proceedings of the 13th International Conference on Intelligent Systems: Theories and Applications, 2020
Online marketplaces such as Amazon allow people to share their experiences about purchased products using textual comments known as product reviews. These reviews have become a common tool that users rely on to get insights on the quality and functionality of products and services from online consumers.
Youssef Esseddiq Ouatiti, Noureddine Kerzazi   +1 more
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Detecting fake reviews through topic modelling

Journal of Business Research, 2022
Against the uncertainty caused by the information overload in the online world, consumers can benefit greatly by reading online product reviews before making their online purchases. However, some of the reviews are written deceptively to manipulate purchasing decisions.
Şule Öztürk Birim, Ipek Kazancoglu, Sachin Kumar Mangla, Aysun Kahraman, Satish Kumar, Yigit Kazancoglu   +5 more
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Ensemble Learning for Detecting Fake Reviews

2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC), 2020
Customers represent their satisfactions of consuming products by sharing their experiences through the utilization of online reviews. Several machine learning-based approaches can automatically detect deceptive and fake reviews. Recently, there have been studies reporting the performance of ensemble learning-based approaches in comparison to ...
Luis Gutierrez-Espinoza, Faranak Abri, Akbar Siami Namin, Keith S. Jones, David R. W. Sears   +4 more
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