Prediction of N-Gram Language Models Using Sentiment Analysis on E-Learning Reviews

Abstract- Sentiment Analysis describes the branch of
the study of Natural Language Processing that seeks to
identify and learn insights from the text or sentences
considered to be reviews or opinions about a product or
service. These opinions are collected from any platforms
like social media, online surveys, online product selling
applications, and blogs, etc. The process of sentiment
analysis roughly starts by collecting the reviews or
opinions, pre-processing of text or sentences, classifying
the text to find the polarity whether it is found to be as
positive, negative, or neutral. The main objective of this
research work is to apply sentiment analysis to the e-
learning review dataset. To attain the above-said objective, we predict which n-gram model best suits in feature extraction with machine learning algorithms.