The cultural impact of fake content is enormous today. Detecting fake content is a crucial step. This research aims to identify fake content using several machine-learning classifiers. Five popular classifiers are used in the experiments: Naïve Bayes, Logistic Regression, Support Vector Machine, Decision Tree and Random Forest. Data cleaning (concatenating the data frame, Shuffling the data, dropping the title and date, converting to lowercase) and pre-processing (Removing punctuation, removing stop words) are the most important methods before using any machine learning classifier. In our research work, different types of models and accuracies were observed. The Decision Tree classifier has gained the highest accuracy, and the Naïve Bayes algorithm has taken very less time to execution.

Naive Bayes, Logistic Regression, Decision Tree and SVM classifier.