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Exploration of Online News Source Data Set using Machine Learning
Creator(s)
McConnell, Kai
Date
May 10, 2019
Department or Program
Computer Science
Advisor(s)
Davis, Janet
Abstract
This paper explores and analyzes the Online News Source dataset from UC Irvine’s dataset repository. In the process multiple new features are added such as word popularity, word embeddings, and parts of speech. These new features are used to create a machine learning model to predict the popularity of each article. The prediction rate as a result of these new features increases dramatically showing the correlation between these features and an article’s success. https://github.com/Kaipie5/FinalProject