Sentimental analysis of Amazon reviews using na?ve bayes on laptop products with MongoDB and R

14th International Conference on Science, Engineering and Technology

自然科学;工业技术

Kamal Hassan, Mohan^1 ; Prasanth Shakthi, Sana^1 ; Sasikala, R.^1

School of Computer Science and Engineering, VIT University, Vellore

632014, India^1

关键词: Branded products;    Data set;    Empirical studies;    Low costs;    Naive-Bayes algorithm;    Online shopping;    Product reviews;    Unstructured data;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/263/4/042090/pdf
DOI  :  10.1088/1757-899X/263/4/042090

来源: IOP

【 摘 要 】

Start In Today's era the e-commerce is developing rapidly these years, buying products on-line has become more and more fashionable owing to its variety of options, low cost value (high discounts) and quick supply systems, so abundant folks intend to do online shopping. In the meantime the standard and delivery of merchandise is uneven, fake branded products are delivered. We use product users review comments about product and review about retailers from Amazon as data set and classify review text by subjectivity/objectivity and negative/positive attitude of buyer. Such reviews are helpful to some extent, promising both the shoppers and products makers. This paper presents an empirical study of efficacy of classifying product review by tagging the keyword. In the present study, we tend to analyse the fundamentals of determining, positive and negative approach towards the product. Thus we hereby propose completely different approaches by removing the unstructured data and then classifying comments employing Naive Bayes algorithm.