Online Product Reviews Based on Sentiment Analysis Online Product Reviews Based on Sentiment Analysis
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Abstract
With the speedy growth of social media on the web, there is a growing amount of information posted to social online services in an audio format, audiovisual format, and textual format in the form of reviews, and comments. People are sharing their views and opinions online. With the rising availability of review sites and blogs, consumers depend on online reviews to make their purchase decisions. A survey found that more than 90% of consumers read online reviews, to judge purchasing decision on consumer products. The sentiment analysis (SA) can be achieved by performing analysis at various levels of the granularity-document level, sentence level, phrase level, and feature level. In this paper, online reviews can be filtered using the SA and repeated incremental pruning to produce error reduction algorithm is presented.
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Research Article
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This is an Open Access article distributed under the terms of the Attribution-Noncommercial 4.0 International License [CC BY-NC 4.0], which requires that reusers give credit to the creator. It allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, for noncommercial purposes only.How to Cite
[1]
“Online Product Reviews Based on Sentiment Analysis: Online Product Reviews Based on Sentiment Analysis”, ajcse, vol. 3, no. 01, Nov. 2018, doi: 10.22377/ajcse.v3i01.101.