Fake News Detection On Social Media Using Machine Learning
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2019 by IJCTT Journal|
|Year of Publication : 2019|
|Authors : P.Ratna Priyanka, M.V.Sumanth|
|DOI : 10.14445/22312803/IJCTT-V67I10P106|
MLA Style:P.Ratna Priyanka, M.V.Sumanth"Fake News Detection On Social Media Using Machine Learning," International Journal of Computer Trends and Technology 67.10 (2019):35-38.
APA Style P.Ratna Priyanka, M.V.Sumanth. Fake News Detection On Social Media Using Machine Learning International Journal of Computer Trends and Technology, 67(10),35-38.
Fake News has an immense impact in our modern society. As a side effect of increasingly popular social media, fake news has emerged as a serious problem afflicting children, teenager and young adults. The main objective is to detect the fake news, which is a classic text classification problem with a straight forward proposition comes up with the applications of NLP (Natural Language Processing) techniques for detecting the `fake news` in social media. By building a model based on a count vectorizer (using word tallies) or a (Term Frequency Inverse Document Frequency) TFIDF matrix, (word tallies relative to how often they’re used in other articles in dataset) can get a solution for this. The result show that Naïve Bayes to detect the Fake News has accuracy approximately 96% , Support Vector Machine achieve the accuracy of 98% and Random Forest achieve the accuracy of 97%.
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Fake news,machine learning,nlp