Big Data and Sentiment Analysis using KNIME: Online Reviews vs. Social Media

被引:0
|
作者
Mihanovic, Ana [1 ]
Gabelica, Hrvoje [1 ]
Krstic, Zivko [1 ]
机构
[1] Poslovna Inteligencija Doo, Zagreb, Croatia
关键词
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暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
引用
收藏
页码:1464 / 1468
页数:5
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