ISSN : 2319-7323

INTERNATIONAL JOURNAL OF COMPUTER SCIENCE ENGINEERING

ABSTRACT

Title	:	A Comparative Study of NLP and Machine Learning Techniques for Sentiment Analysis and Topic Modeling on Amazon Reviews
Authors	:	Gina V. Acosta Gutiérrez
Keywords	:	Machine Learning, Text Mining, NLP, Sentiment Analysis, Online Reviews
Issue Date	:	Mar-Apr 2020
Abstract	:	Nowadays, due to the growth on the offer of online products, a large amount of information is available on internet can be found, especially from the reviews written by users who have purchased products on online platforms. It is possible to analyze these reviews in order to extract useful information about the user's opinion about a product. The present paper consists of the development of a model based on machine learning techniques in order to identify trends patterns of online products based on technical data, which in the present case would be the products that are available in the electronic commerce platform Amazon. Several authors have highlighted the importance of analyzing comments, reviews or any type of feedback obtained from users for sellers or a company that offers its products in online trading platforms. This paper consists of creating a model that uses various machine learning techniques in order to generate useful information for salespeople. In this way, the machine learning model will be able to identify the opinion of a user based on its review and determine if this user qualified the product in a positive or negative way.
Page(s)	:	159-170
ISSN	:	2319-7323
Source	:	Vol. 9, No. 2
DOI	:	10.21817/ijcsenet/2020/v9i2/200902007