Analysis of Various Opinion Mining Algorithms

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2015 by IJCTT Journal
Volume-22 Number-2
Year of Publication : 2015
Authors : Gayathri R Krishna, Kavitha S, Yamini S, Rekha A
  10.14445/22312803/IJCTT-V22P114

MLA

Gayathri R Krishna, Kavitha S, Yamini S,Rekha A "Analysis of Various Opinion Mining Algorithms". International Journal of Computer Trends and Technology (IJCTT) V22(2):72-75, April 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
Online reviews, blogs, and discussion forums such as WebMD on chronic diseases and medicines are becoming important supporting resources for patients. Extracting useful information from these substantial bodies is very difficult and challenging. Opinion mining or sentiment analysis involves the extraction of useful information (e.g., positive or negative sentiments of a product) from a large quantity of text opinions or reviews authored by Internet users. Various algorithms had been proposed to extract information from the opinion of internet users. Some of the algorithms are LDA, sLDA, NMF, SSNMF, DiscLDA and PAAM. In this paper, we are discussing and analysing these opinion mining algorithms.

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Keywords
Opinion mining, text mining, topic modelling, aspect mining.