Aspect-Based Sentiment Analysis on Amazon Product Reviews

  • Muhammad Abubakar COMSATS University Islamabad Abbottabad Campus Pakistan, Pakistan
  • Amir Shahzad COMSATS University Islamabad Abbottabad Campus Pakistan, Pakistan
  • Husna Abbasi COMSATS University Islamabad Abbottabad Campus Pakistan, Pakistan
Keywords: Naïve bayes, Text Classification Algorithms, Natural Language Processing, Support Vector Machines, NLP, SVM


The focus of this paper was on Amazon product reviews. The goal of this is to study is two (NLP) for evaluating Amazon product review sentiment analysis. Customers can learn about a product's quality by reading reviews. Several product review characteristics, such as quality, time of evaluation, material in terms of product lifespan and excellent client feedback from the past, will have an impact on product rankings. Manual
interventions are required to analyse these reviews, which are not only time consuming but also prone to errors. As a result, automatic models and procedures are required to effectively manage product reviews. (NLP) is the most practical method for training a neural network in this era of artificial intelligence. First, the Naive Bayes classifier was used to analyse the sentiment of consumer in this study. The (SVM) has categorized
user sentiments into binary categories. The goal of the approach is to forecast some of the most important characteristics of an amazon-based product reviews, and then analyse Customer attitudes about these aspects. The suggested model is validated using a large-scale real-world dataset gathered specifically for this purpose. The dataset is made up of thousands of manually annotated product reviews gathered from amazon. After passing the input via the network model, (TF) and (IDF) pre-processing methods were used to evaluate the feature. The outcomes precision, recall
and F1 score are very promising


Bhatt, A., Patel, A., Chheda, H., & Gawande, K. (2015). Amazon review classification
and sentiment analysis. International Journal of Computer Science and Information
Technologies, 6(6), 5107-5110.
Dadhich, A., & Thankachan, B. (2022). Sentiment analysis of amazon product reviews
using hybrid rule-based approach. In Smart Systems: Innovations in
Computing (pp. 173-193). Springer, Singapore.
Dey, S., Wasif, S., Tonmoy, D. S., Sultana, S., Sarkar, J., & Dey, M. (2020, February). A
comparative study of support vector machine and Naive Bayes classifier for
sentiment analysis on Amazon product reviews. In 2020 International Conference
on Contemporary Computing and Applications (IC3A) (pp. 217-220). IEEE.
Fang, X., & Zhan, J. (2015). Sentiment analysis using product review data. Journal of
Big Data, 2(1), 1-14.
Haque, T. U., Saber, N. N., & Shah, F. M. (2018, May). Sentiment analysis on large scale
Amazon product reviews. In 2018 IEEE international conference on innovative
research and development (ICIRD) (pp. 1-6). IEEE.
Jagdale, R. S., Shirsat, V. S., & Deshmukh, S. N. (2019). Sentiment analysis on product
reviews using machine learning techniques. In Cognitive informatics and soft
computing (pp. 639-647). Springer, Singapore.
Joseph, R. P. S. (2020). Amazon Reviews Sentiment Analysis: A Reinforcement Learning
Approach (Doctoral dissertation, MS Thesis, Griffith College Dublin, Ireland).
Karthikayini, T., & Srinath, N. K. (2017, December). Comparative polarity analysis on
Amazon product reviews using existing machine learning algorithms. In 2017
2nd International Conference on Computational Systems and Information Technology
for Sustainable Solution (CSITSS) (pp. 1-6). IEEE.
More, G., Behara, H., & Suresha, A. M. (2020). Sentiment Analysis on Amazon Product
Reviews with Stacked Neural Networks. no. October.
Pandey, P., & Soni, N. (2019, February). Sentiment analysis on customer feedback data:
Amazon product reviews. In 2019 International Conference on Machine Learning,
Big Data, Cloud and Parallel Computing (COMITCon) (pp. 320-322). IEEE.
Rain, C. (2013). Sentiment analysis in amazon reviews using probabilistic machine
learning. Swarthmore College.
Salmony, M. Y. A., & Faridi, A. R. (2021, April). Supervised Sentiment Analysis on
Amazon Product Reviews: A survey. In 2021 2nd International Conference on
Intelligent Engineering and Management (ICIEM) (pp. 132-138). IEEE.
Xiao, Y., Qi, C., & Leng, H. (2021, March). Sentiment analysis of Amazon product
reviews based on NLP. In 2021 4th International Conference on Advanced
Electronic Materials, Computers and Software Engineering (AEMCSE) (pp. 1218-
1221). IEEE
How to Cite
M. Abubakar, A. Shahzad, and H. Abbasi, “Aspect-Based Sentiment Analysis on Amazon Product Reviews”, INJIISCOM, vol. 2, no. 2, pp. 94-99, Dec. 2021.