Artificial Neural Network Utilization for Analyzing Sentiment Polarity in Electronics Product Reviews

Abstract

Intelligent systems currently have been proven to provide more benefits on various aspects of human life. One of them is sentiment analysis (SA) approach. SA is a mathematical approach that allows machines to analyze the opinion polarity of the statements or documents. Generally, SA is utilized to observe the tendency of public opinion on an issue. SA can also be used on e-commerce to analyze the trend of customer statements toward a product based on the reviews given by them. Thus, SA will help e-commerce business owners to know the level of acceptance toward offered products. In this paper, we try to evaluate the artificial neural network (ANN) algorithm in conducting a SA of electronic products reviews. In this study, the ANN was designed using 1 input layer, 1 hidden layer consisting of 10 neurons, and 1 output layer consisting of 2 neurons. Our experimental results showed that the ANN had a fairly high accuracy and precision while conducting SA toward electronic products reviews that have been carried out, i.e. 70.80% and 71.07% respectively. Hence, ANN is very possible to be applied to intelligent systems that are tasked to assist e-commerce business owners in conducting SA toward feedback provided by the customers.