Sentiment Analysis of Facebook Comments Using Various Machine Learning Techniques

The measure of information that is created has risen consistently and an ever increasing number of sorts of data are being put away in unstructured or semi-organized configurations. Slant Analysis is the way toward extricating emotional data from online inputs. Assumption examination empowers PCs to mechanize the exercises performed by human by settling on choices dependent on suppositions of the remarks or post in online media locales. In this paper we have evaluated the sentiments of facebook comments using five different machine learning techniques, Naïve Bayes, SVM, Random Forest, KNN and Decision tree. Evaluated these five classifiers using different performance measures like Precision , Recall and F1-score. Beneficiaries of this paper are researchers, teachers, and students who have keen interest in the topic