A COMPARATIVE PERFORMANCE EVALUATION OF SEARCH ITEMS AND
EXPERIENCE ITEMS IN AMAZON COSTUMER REVIEWS
Farhad Khoshbakht
Department of Computer Science, Jamia Millia Islamia (A Central University), New Delhi, India
110025
f.khoshbakht630@gmail.com
Atena Shiranzaei
Department of Computer Engineering, Faculty of Industry and Mining(Khash), University of Sistan
and Baluchestan,Zahedan,Iran
ashiranzaei@eng.usb.ac.ir
S. M. K. Quadri
Department of Computer Science, Jamia Millia Islamia(A Central University), New Delhi, India
110025
3quadrismk@jmi.ac.in
ABASTRACT
The accelerated growth of web users alongside developing the influence of online review web page
and social media has brought forth sentiment analysis assessment mining, which targets understanding
what others think, assessments, comments and reviews about the item in social media, E-Commences
sites, and so forth. The product review comments contributed by the costumers have rich data about
the use of the products. In this article, we have gathered reviews from Amazon.com by separating
search items from experience items and we inspect the business effect of online reviews on products
sales performance. This article looks at the impact of the degree of detail in an item review and the
degree of analyst concurrence with it on the creditability of a review and customers’ procurement
expectations for search and experience items.
Keywords: Product Reviews, Sentiment Analysis, Online Reviews, Search Items, Experience Items.