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Fraudulent News Detection on Social Media

Mahajan, Archana Uday (2022) Fraudulent News Detection on Social Media. Masters thesis, Dublin, National College of Ireland.

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Today, technological advances and easy and open access to the Internet and social media have increased the international dissemination of information and news through social networks. In many cases, social media has become a primary source of information for the general public, governments and brands. Online posts are valuable and important because they can deliver news and reach even the most remote regions and people quickly and efficiently. These days, with the power of social media to reach and influence such a large audience, we realize that a lot of fake news and information is causing confusion and disorder in people’s minds. The objective of this research is to identify fraudulent news in social media posts, to increase the reliability of online news, and determine how text analysis and machine or deep learning algorithms will work together to make the outcome more accurate. This research focuses on using natural language processing, text recognition, analytics, and machine learning techniques to separate fraudulent and genuine content from a dataset created by combining various Kaggle datasets, with an accuracy score of 97% from ML models and 94% using BERT.

Item Type: Thesis (Masters)
Uncontrolled Keywords: NLP; Machine Learning; LSTM; Naive Bayes; BERT; RNN
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
P Language and Literature > P Philology. Linguistics > Computational linguistics. Natural language processing
Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4150 Computer Network Resources > The Internet > World Wide Web
T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Telecommunications > The Internet > World Wide Web
Divisions: School of Computing > Master of Science in Data Analytics
Depositing User: Tamara Malone
Date Deposited: 22 Feb 2023 16:57
Last Modified: 02 Mar 2023 09:31

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