• DocumentCode
    251948
  • Title

    The Evaluation of the Public Opinion - A Case Study: MERS-CoV Infection Virus in KSA

  • Author

    Zarrad, Anis ; Jaloud, Abdulaziz ; Alsmadi, Izzat

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Syst., Prince Sultan Univ., Riyadh, Saudi Arabia
  • fYear
    2014
  • fDate
    8-11 Dec. 2014
  • Firstpage
    664
  • Lastpage
    670
  • Abstract
    Opinion Mining and Sentiment Analysis are active research trends in natural language processing and data mining. Recently, this research has been extended outside the computer science area to cover other areas such as social science, political science, and business. The explosion of social media such as social networks, Blogs, Twitter, and forums has created unprecedented opportunities for data mining research community. Analyzers can study and analyze users´ opinions, attitudes, and emotions about news or social events. Big data focuses on the intelligent analysis of a large amount of data that is typically collected from several different sources. Our focus in this work is to address new challenges raised by combining Apache Hadoop as a big data platform with an opinion mining approach to make a decision we often seek based on collected data from the opinions of people. We presented a case study about MERS virus in KSA to evaluate our proposed approach. A discussion of available dataset and results are also provided.
  • Keywords
    Big Data; data mining; natural language processing; social networking (online); Apache Hadoop; Big Data; Blogs; KSA; MERS-CoV infection virus; Twitter; data mining research community; intelligent analysis; natural language processing; opinion mining; public opinion; sentiment analysis; social media; social networks; Big data; Classification algorithms; Computer science; Data mining; Sentiment analysis; Twitter; Big Data; Hadoop; MERS-CoV infection Virus; Opinion mining; Social Networks; sentimental analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Utility and Cloud Computing (UCC), 2014 IEEE/ACM 7th International Conference on
  • Conference_Location
    London
  • Type

    conf

  • DOI
    10.1109/UCC.2014.107
  • Filename
    7027574