Detection of Fake News and Probability

1Sireddy.Naveen Kumar Reddy, Dr.M.Sujatha

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Abstract:

The quality of information is an important issue in the present age. Preciseness of news or information through social media is very important and it is an increasing problem in our society. Fake news is the misleading or wrong information that is spread over the internet to damage the popularity of person or organization. To overcome the problem, research should be done to classify whether the news is ‘Real’ or ‘Fake’. To classify the news, a machine learning algorithm is adopted. In the process of classifying news classifier algorithm like Support Vector Machine algorithm, Naive Bayes algorithm, Decision Tree algorithm, Random Forest algorithm, and Logistic regression classifier algorithm are required. Initially data sets are extracted and it should be processed by the machine learning algorithms. Buzzfeed, Credbank, Phema are some of the datasets which can extract the required information from social media. In our model the contents are processed through all the algorithms which will predict whether the news on social media is ‘Fake’ or ‘Real’ and the probability of truth.

Keywords:

Fake news, classifier, machine learning, data sets.

Paper Details
Month2
Year2020
Volume24
IssueIssue 2
Pages5778-5785