Open AccessSentiment analysis: a challenge
Author(s) -
Ekta Gupta,
Ashok Kumar,
Manish Kumar
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.27.16288
Subject(s) - sentiment analysis , computer science , product (mathematics) , sentence , data science , polarity (international relations) , process (computing) , work (physics) , quality (philosophy) , natural language processing , artificial intelligence , mechanical engineering , philosophy , genetics , geometry , mathematics , epistemology , biology , engineering , cell , operating system
Sentiment analysis or judgment/thoughts mining is one of the major jobs of NLP (Natural Language Processing). Sentiment analysis has acquired much awareness in recent years. In this paper, our focus is to approach the problem of sentiment polarity assortment, which is one of the elementary problems of sentiment analysis. A general process for sentiment polarity assortment is considered with complete procedure explanation. Data used in this research are online buying product reviews collected from the shopping platform Amazon.com. Experiments for both sentence-level assortment and review-level assortment are executed with guarantee outcomes. Sentiment analysis will help to enhance the business with its performance of giving accurate result .In the end; we also give awareness into our future work on sentiment analysis. From last decade there is no such work has done on sentiment analysis to improve the product quality on the basis of what the customer needs and sometimes it is introduce as opinion mining while the importance in this case is on extraction.