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
Link To Document :
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