Abstract: Opinion mining (known as sentiment analysis or emotion Artificial Intelligence) holds important roles for e-commerce and benefits to numerous business and organizations. It studies the use of natural language processing, text analysis, computational linguistics, and biometrics to provide us business valuable insights into how people feel about our product brand or service. In this study, we investigate reviews from Amazon Fine Food Reviews dataset including about 500,000 reviews and propose a method to transform reviews into features including Opinion Words which then can be used for reviews classification tasks by machine learning algorithms. From the obtained results, we evaluate useful Opinion Words which can be informative to identify whether the review is positive or negative.

Phuc Quang Tran, Ngoan Thanh Trieu, Nguyen Vu Dao, Hai Thanh Nguyen and Hiep Xuan Huynh, “Effective Opinion Words Extraction for Food Reviews Classification” International Journal of Advanced Computer Science and Applications(IJACSA), 11(7), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110755

@article{Tran2020,
title = {Effective Opinion Words Extraction for Food Reviews Classification},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110755},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110755},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {7},
author = {Phuc Quang Tran and Ngoan Thanh Trieu and Nguyen Vu Dao and Hai Thanh Nguyen and Hiep Xuan Huynh}
}