• DocumentCode
    2273015
  • Title

    Review analyzer: Analyzing consumer product reviews from review collections

  • Author

    Arun Manicka Raja, M. ; Winster, S.G. ; Swamynathan, S.

  • Author_Institution
    Dept. of Inf. Sci. & Technol., Anna Univ., Chennai, India
  • fYear
    2012
  • fDate
    25-27 April 2012
  • Firstpage
    287
  • Lastpage
    292
  • Abstract
    E-transactions have become prominent and highly convenient due to the widespread usage of the internet. The number of consumer reviews on various products is increasing day-by-day. These vast number of reviews are beneficial to manufacturers and consumers alike. It is a challenging task for a potential consumer to read all reviews to make a better purchase decision. It is beneficial to mine available consumer reviews for popular products from various consumer product review sites. The first step to do this is to decide the polarity of a review by performing sentiment analysis. We can then classify the review based on the polarity. This paper presents a comparison of a sentiment analyzer with other existing classifiers.
  • Keywords
    Internet; data mining; text analysis; Internet; Web text analysis; consumer product reviews; e-transactions; review analyzer; review collections; sentiment analysis; text mining; Consumer products; Crawlers; Data mining; Machine learning; Machine learning algorithms; Memory; XML; Information filtering; Information visualization; Text mining; Web Search; Web text analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Recent Advances in Computing and Software Systems (RACSS), 2012 International Conference on
  • Conference_Location
    Chennai
  • Print_ISBN
    978-1-4673-0252-4
  • Type

    conf

  • DOI
    10.1109/RACSS.2012.6212682
  • Filename
    6212682