Feature extracted sentiment analysis of customer product reviews

Devasia, Neena; Sheik, Reshma

doi:10.1109/icett.2016.7873646

Cited by 14 publications

(2 citation statements)

References 3 publications

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“…The proposed work concentrated only on extracting explicit aspects. Devasia & Sheik (2016) identified aspects with the help of dependency between the words of review sentences. Stanford dependency parser is used to identify the relationship between the words.…”

Section: Sentiment Analysismentioning

confidence: 99%

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Aspect-based classification of product reviews using Hadoop framework

Rodrigues¹,

Chiplunkar²,

Fernandes³

2020

Cogent Engineering

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The advancement of e-commerce along with the quick development of product review discussion in the most recent decade, an enormous measure of sentiment data or reviews are produced which made it practically difficult for a customer to take an educated buy choice. A good number of customers share their conclusions about the product during these days. These reviews have an important role in customers' purchase-decision process. For a popular product there may be hundreds or thousands of reviews. This is difficult for a potential customer to go to each of them to make an educated choice on whether to buy the product or not. Also, this is difficult for manufacturer of the product to follow-up and to manage client opinions. In this scenario, the aspects-based sentimental analysis helps in analyzing the reviews and categorizing them into appropriate aspects. Aspect or feature refers to attributes or qualities of a product. The proposed work begins with collecting reviews from online shopping websites, identifying aspects and classifying opinion orientation of aspects with different sentiment analysis techniques using Hadoop framework. This paper proposes a new pattern-based method for aspect extraction and sentiment analysis which gives an accuracy in the ABOUT THE AUTHORS

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Section: Sentiment Analysismentioning

confidence: 99%

“…The experimental results showed that the syntactic pattern approach had several weaknesses that need to be improved. Devasia & Sheik (2016) Semantic-based approach Proposed semantic-based approach for extracting product aspects. Recursive deep analyzer is used to find out opinion orientation of Product review sentences.…”

Section: Maharani Et Al (2015)mentioning

confidence: 99%