A CLASSIFIED SENTIMENT STUDY OF E –COMMERCE ANALYSES BY MINING DEPENDENCY IN PRODUCT FEATURES AND IDEAS IN SOCIAL NETWORK

Abstract

Abstract:  In actual world, web analysis performs an important role in understanding the data and information discovery from the real input records. In internet sentiment evaluation, information the data and information discovery are the vital components of records mining method. In analyzing the records, the relevant information are extracted and used for prediction in data mining. In relevant records extraction, sentiment prediction performs the function of identifying the fairly applicable functions from the unique statistics. This research particularly focuses on web sentiment evaluation strategies to enhance the accuracy of prediction accuracy. clients decide upon and willing to the reliability of consumer reviews and dependability of the users who publish within the e-commerce internet web sites. based on sentiment evaluation of large – scale textual content opinions on e-trade websites, centered on sentiment similarity among customers to set up their believe, that may provide guide for further implementation of believe associated advice provider.