Abstract—At this current digital era, business platforms have
been drastically shifted toward online stores on internet. With
the internet-based platform, customers can order goods easily
using their smart phones and get delivery at their place without
going to the shopping mall. However, the drawback of this
business platform is that customers do not really know about
the quality of the products they ordered. Therefore, such
platform service often provides the review section to let
previous customers leave a review about the received product.
The reviews are a good source to analyze customer's satisfaction.
Business owners can assess review trend as either positive or
negative based on a feedback score that customers had given,
but it takes too much time for human to analyze this data. In
this research, we develop computational models using machine
learning techniques to classify product reviews as positive or
negative based on the sentiment analysis. In our experiments,
we use the book review data from amazon.com to develop the
models. For a machine learning based strategy, the data had
been transformed with the bag of word technique before
developing models using logistic regression, naïve bayes,
support vector machine, and neural network algorithms. For a
deep learning strategy, the word embedding is a technique that
we used to transform data before applying the long short-term
memory and gated recurrent unit techniques. On comparing
performance of machine learning against deep learning models,
we compare results from the two methods with both the
preprocessed dataset and the non-preprocessed dataset. The
result is that the bag of words with neural network outperforms
other techniques on both non-preprocess and preprocess
Index Terms—Sentiment analysis, text classification, machine learning, deep learning.
Pumrapee Poomka, Nittaya Kerdprasop, and Kittisak Kerdprasop are with the School of Computer Engineering, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand (e-mail: firstname.lastname@example.org, email@example.com, firstname.lastname@example.org).
Cite: Pumrapee Poomka, Nittaya Kerdprasop, and Kittisak Kerdprasop, "Machine Learning Versus Deep Learning Performances on the Sentiment Analysis of Product Reviews," International Journal of Machine Learning and Computing vol. 11, no. 1, pp. 103-109, 2021.Copyright © 2021 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).