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Title: Deep learning-based fake news detection
Authors: Chen, Hanzhi
Keywords: Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Chen, H. (2022). Deep learning-based fake news detection. Master's thesis, Nanyang Technological University, Singapore.
Abstract: Identifying the truthfulness of news is crucial as it has a great societal impact, and its importance has increased every year since the information age. After the deep learning models were introduced to generate fake news, it become more difficult for a human to identify fake news. Therefore, researchers proposed neural network models to detect fake news but most models only focus on a few datasets. This dissertation evaluates different types of methods on various datasets for overall performance. Furthermore, we discuss the application range of different types of detection methods.
Schools: School of Electrical and Electronic Engineering 
Research Centres: Rapid-Rich Object Search (ROSE) Lab 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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