%0 Journal Article %1 noauthororeditor %A Sharma, Nikhil %D 2020 %J International Journal of Trend in Scientific Research and Development %K Classification Fake-news Filtering Machine Natural algorithms detection language learning processing %N 4 %P 1317-1320 %T Fake News Detection using Machine Learning %U https://www.ijtsrd.com/computer-science/other/31148/fake-news-detection-using-machine-learning/nikhil-sharma %V 4 %X Indian politics suffered from a great set back due to fake news. Fake news is intentionally written to mislead the audience to believe the false propaganda, which makes it difficult to detect based on news content. The fake news has hindered the mindset of the common people. Due to this widespread of the fake news online it is the need of the hour to check the authenticity of the news. The spread of fake news has the potential for extremely negative impact on society. The proposed approach is to use machine learning to detect fake news. Using vectorisation of the news title and then analysing the tokens of words with our dataset. The dataset we are using is a predefined curated list of news with their property of being a fake news or not. Our goal is to develop a model that classifies a given article as either true or fake. General Terms Fake News, Self Learning, Pattern Matching, Response Generation, Artificial Intelligence, Natural Language Processing, Context Free Grammar, Term Frequency Inverse Document Frequency, Stochastic Gradient Decent, Word2Vec. Nikhil Sharma "Fake News Detection using Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31148.pdf Paper Url :https://www.ijtsrd.com/computer-science/other/31148/fake-news-detection-using-machine-learning/nikhil-sharma

@article{noauthororeditor, abstract = {Indian politics suffered from a great set back due to fake news. Fake news is intentionally written to mislead the audience to believe the false propaganda, which makes it difficult to detect based on news content. The fake news has hindered the mindset of the common people. Due to this widespread of the fake news online it is the need of the hour to check the authenticity of the news. The spread of fake news has the potential for extremely negative impact on society. The proposed approach is to use machine learning to detect fake news. Using vectorisation of the news title and then analysing the tokens of words with our dataset. The dataset we are using is a predefined curated list of news with their property of being a fake news or not. Our goal is to develop a model that classifies a given article as either true or fake. General Terms Fake News, Self Learning, Pattern Matching, Response Generation, Artificial Intelligence, Natural Language Processing, Context Free Grammar, Term Frequency Inverse Document Frequency, Stochastic Gradient Decent, Word2Vec. Nikhil Sharma "Fake News Detection using Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31148.pdf Paper Url :https://www.ijtsrd.com/computer-science/other/31148/fake-news-detection-using-machine-learning/nikhil-sharma }, added-at = {2020-07-16T12:14:09.000+0200}, author = {Sharma, Nikhil}, biburl = {https://www.bibsonomy.org/bibtex/29f9c37232405419ea070c813268fa5aa/ijtsrd}, interhash = {67c3cddc92a457e39deb0a3a8fc262c1}, intrahash = {9f9c37232405419ea070c813268fa5aa}, issn = {2456-6470}, journal = {International Journal of Trend in Scientific Research and Development}, keywords = {Classification Fake-news Filtering Machine Natural algorithms detection language learning processing}, language = {English}, month = {june}, number = 4, pages = {1317-1320}, timestamp = {2020-07-16T12:14:09.000+0200}, title = {Fake News Detection using Machine Learning }, url = {https://www.ijtsrd.com/computer-science/other/31148/fake-news-detection-using-machine-learning/nikhil-sharma}, volume = 4, year = 2020 }