Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/1053
Title: Applying Machine Learning to Detect Fake News
Authors: Subhabaha Pal, T. K. Senthil Kumar
Keywords: Count Vectorizer
Machine Learning
Fake news detection
NLP
TFIDF Vectorizer
Text Analytics
Issue Date: 2019
Publisher: Indian Journal of Computer Science
Abstract: Spread of fake news has become a big problem in recent times and this has become a source of discomfort in the society in many instances. Application of sophisticated Machine Learning algorithms for detection of fake news has shown some success and it is a new area which shows immense opportunities for practical use and further research. The detection of fake news using machine learning algorithms have been discussed in details in this paper. News items are unstructured data and this paper shows how unstructured news items can be turned into structured form using Count vectorization and TFIDF vectorization techniques. This paper also shows how machine learning models can be developed and the classification can be done using the newly structured data employing sophisticated developed Machine Learning algorithms.
URI: http://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/1053
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