• DocumentCode
    185679
  • Title

    Big data and sentiment analysis using KNIME: Online reviews vs. social media

  • Author

    Minanovic, Ana ; Gabelica, Hrvoje ; Krstic, Zivko

  • Author_Institution
    Poslovna inteligencija d.o.o., Zagreb, Croatia
  • fYear
    2014
  • fDate
    26-30 May 2014
  • Firstpage
    1464
  • Lastpage
    1468
  • Abstract
    Text analytics and sentiment analysis can help an organization derive potentially valuable business insights from text-based content such as word documents, email and postings on social media streams like Facebook, Twitter and LinkedIn. The system described here analyses opinions about various gadgets collected from two different sources and in two different forms; online reviews and Twitter posts (tweets). Sentiment analysis can be applied to online reviews in easier and more detailed way than to the tweets. Namely, online reviews are written in clear and grammatically more accurate form, while in tweets, internet slang, sarcasm and allegory are often used. System described here explains methods of data collection, sentiment analysis process for online reviews and tweets using KNIME, gives an overview of differences and analysis possibilities in sentiment analysis for both data sources.
  • Keywords
    data mining; social networking (online); text analysis; Facebook; Internet slang; KNIME; LinkedIn; Twitter; allegory; big data; business insights; data collection; email; online reviews; sarcasm; sentiment analysis process; social media streams; text analytics; text-based content; word documents; Databases; Dictionaries; Internet; Media; Sentiment analysis; Tag clouds; Twitter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Communication Technology, Electronics and Microelectronics (MIPRO), 2014 37th International Convention on
  • Conference_Location
    Opatija
  • Print_ISBN
    978-953-233-081-6
  • Type

    conf

  • DOI
    10.1109/MIPRO.2014.6859797
  • Filename
    6859797