Evaluation of Social Human Sentiment Analysis Using Machine Learning Algorithms

Abstract

AbstractThe impact of social networking on human beings is significantly increasing in daily life, academics, sports, business, and amusement. Sentiment analysis becomes easier with the availability of comments or reviews on social media. Sentiment analysis is opinion mining, which analyzes the sentiment of the person based on the comments as input using machine learning algorithms. People are generic to go through the review comments before exploring any new venture. As a result, a consumer's social media review is very valuable for new customers. In this paper, sentiment analysis is carried out based on the restaurant review comments available in the social networks for experimental purposes. The corpora of features are prepared using natural language processing and a bag of words model. The objective of this paper is to present the comparison between learning, training, and classifying the restaurant review data based on the evaluation of the proposed model using six different machine learning algorithms. Inference of these training and testing is presented with a bar graph for straightforward comparative study. This research concludes with a proper selection of the best-fit machine learning algorithm.KeywordsSentiment analysisRestaurant reviewClassificationMachine learning algorithm