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Fake News Detection Using Deep Learning and Computational Linguistics

Sahay, Neil (2022) Fake News Detection Using Deep Learning and Computational Linguistics. Masters thesis, Dublin, National College of Ireland.

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Though the growth of the internet in the twenty-first century has resulted in significant advancements in many areas, including education, research, and information dissemination, it has also had several negative consequences. While the popularity of social media skyrocketed in 2007 with the introduction of Facebook, the number of social media users has risen substantially since then, resulting in increased dissemination of fake news, which in turn causes societal instability. Manual tracking is difficult as information is vulnerable to a variety of language used by users, such as hilarious content, which is not always considered fake news. While there has been research done in this sector to apply Artificial Intelligence to minimize this recurring issue, it has mainly backtracked owing to the provision of inadequate data and usage of supervised learning algorithms. By integrating artificial intelligence approach with innovative Natural Language Processing (NLP) techniques such as Recurrent Convolutional Neural Network (R-CNN) and Long Short-Term Memory (LSTM), and this study helped in overcoming the difficulty of correctly classifying fake and real content by achieving 95% accuracy, therefore assisting in the tracking and removal of illegal and misleading information.

Item Type: Thesis (Masters)
Uncontrolled Keywords: RCNN; LSTM; Fake news; Real News; Lemmatization
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence
Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence
P Language and Literature > P Philology. Linguistics > Computational linguistics. Natural language processing
Divisions: School of Computing > Master of Science in Data Analytics
Depositing User: Tamara Malone
Date Deposited: 10 Mar 2023 15:47
Last Modified: 10 Mar 2023 15:47

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