Methods And Challenges of Using Data Analytics to Combat Fake News

Mandala, Sreevishnuvardhan (2024) Methods And Challenges of Using Data Analytics to Combat Fake News. Masters thesis, Dublin, National College of Ireland.

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Abstract

The research's main purpose focuses on the utilization of machine learning algorithms for identifying and preventing fake news in digital media. In this context, the study adopts a quantitative research design and includes four machine learning algorithms, Logistic Regression, Gradient Boosting Machines, Support Vector Machines, and Random Forests, the dataset used is from open access. Thus, the methodology includes an increased level of feature engineering to extract textual and contextual features from news articles that will help in spotting misinformation. Model performance is assessed from accuracy, precision, recalls, and F1-score, although sample validation and cross-validation are used to improve transcription. This research also adheres to ethical issues such as data privacy issues, bias, and transparency issues. It is hoped that the findings will help in enhancing the effectiveness of fake news detection models to improve the credibility of new and social media. Therefore, this study depicts that this is the key solution to reducing the quantity of fake news prevalent on the network.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Muntean, Cristina Hava UNSPECIFIED
Uncontrolled Keywords:	Fake news; machine learning; data analytics; Logistic regression; SVM; Random Forests; GBM; misinformation detection
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 > Websites > Online social networks T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Telecommunications > The Internet > World Wide Web > Websites > Online social networks
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	03 Sep 2025 11:51
Last Modified:	03 Sep 2025 11:51
URI:	https://norma.ncirl.ie/id/eprint/8741

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