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Volume & Issue no: Volume 3, Issue 6, November - December 2014

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Title:
A Survey on Detection of Shill Reviews by Measuring its Linguistic Features
Author Name:
Sarika S. Nalawade, Ms. S. S. Pawar
Abstract:
Abstract With the increasing use of online shopping; e-commerce websites have become targets of opinion spam. People can now post their views using Internet forums, discussion groups, product reviews and blogs, which are collectively called usergenerated contents. Scanning through large amounts of usergenerated content manually and checking its truthfulness is time-consuming and sometime impossible. This study explores the various types of linguistic features of shill reviews and respected tools developed to extract product features from text of product reviews. Sentiment analysis, Natural language processing, Machine learning techniques and linguistic features can be employed to detect the shill reviews. The main objective of review spammers is to mislead users and change their perception about particular product or service. Various linguistic characteristics including styles of spamming can be helpful to detect the review spam. Different methods according to linguistic features have been adopted and implemented effectively. Review manipulation was found on reputable e-commerce websites, so linguistic-feature based methods have gained popularity. Keywords:- Shill reviews, Informativeness, Readability, Linguistic features, Subjectivity
Cite this article:
Sarika S. Nalawade, Ms. S. S. Pawar , " A Survey on Detection of Shill Reviews by Measuring its Linguistic Features" , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) , Volume 3, Issue 6, November - December 2014 , pp. 269-272 , ISSN 2278-6856.
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NOTE: Authors note that paper cannot be withdrawn at any condition once it is accepted. The Team of IJETTCS advise you, do not submit same article to the multiple journals simultaneously. This may create a problem for you. Please wait for review report which will take maximum 01 to 02 week. 

 

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International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
ISSN 2278-6856
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