• DocumentCode
    266877
  • Title

    Numeric rating of Apps on Google Play Store by sentiment analysis on user reviews

  • Author

    Islam, Md Rafiqul

  • Author_Institution
    Dept. of Comput. Sci., American Int. Univ. - Bangladesh, Dhaka, Bangladesh
  • fYear
    2014
  • fDate
    10-12 April 2014
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The sudden eruption of sentiment analysis and opinion mining has opened new possibilities to improve our information gathering interests. We are always keen to know what others say about the devices or applications we are going to use. Its observed that sometimes the numeric rating has vast difference than the reviews given by the users. To remove this ambiguity a unified rating system has been proposed here. The starred rating and a generated numeric polarity of the reviews are combined to generate the final rating. The proposition is based on sentiment analysis and an optimized probabilistic approach described by a group of researchers. The approach is proved for its efficiency in a diverse corpus of writings where the targets are of different categories.
  • Keywords
    Internet; data mining; Apps; Google Play Store; diverse corpus; numeric rating; opinion mining; optimized probabilistic; sentiment analysis; starred rating; unified rating system; user reviews; Feature extraction; Google; Knowledge discovery; Probabilistic logic; Sentiment analysis; Writing; Apps Review; Numeric Rating; Polarity Extraction; Sentiment Analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Engineering and Information & Communication Technology (ICEEICT), 2014 International Conference on
  • Conference_Location
    Dhaka
  • Print_ISBN
    978-1-4799-4820-8
  • Type

    conf

  • DOI
    10.1109/ICEEICT.2014.6919058
  • Filename
    6919058