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Sentimental analysis of Amazon reviews using naïve bayes on laptop products with MongoDB and R
Kamal Hassan M, Prasanth Shakthi S,
Published in IOP Publishing
Volume: 263
Issue: 4
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. © Published under licence by IOP Publishing Ltd.
About the journal
JournalData powered by TypesetIOP Conference Series: Materials Science and Engineering
PublisherData powered by TypesetIOP Publishing
Open AccessYes