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

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.