Abstract
Twitter is a micro-blogging service built to discover what is happening at any moment in time, anywhere in the world. Twitter messages are short, generated constantly, and well suited for knowledge discovery using data stream mining. We introduce MOA-TweetReader, a system for processing tweets in real time. We show two main applications of the new system for studying Twitter data: detecting changes in term frequencies and performing real-time sentiment analysis.
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Bifet, A., Holmes, G., Pfahringer, B. (2011). MOA-TweetReader: Real-Time Analysis in Twitter Streaming Data. In: Elomaa, T., Hollmén, J., Mannila, H. (eds) Discovery Science. DS 2011. Lecture Notes in Computer Science(), vol 6926. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24477-3_7
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DOI: https://doi.org/10.1007/978-3-642-24477-3_7
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