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Sentiment Knowledge Discovery in Twitter Streaming Data

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Discovery Science (DS 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6332))

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Abstract

Micro-blogs are a challenging new source of information for data mining techniques. 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, and generated constantly, and well suited for knowledge discovery using data stream mining. We briefly discuss the challenges that Twitter data streams pose, focusing on classification problems, and then consider these streams for opinion mining and sentiment analysis. To deal with streaming unbalanced classes, we propose a sliding window Kappa statistic for evaluation in time-changing data streams. Using this statistic we perform a study on Twitter data using learning algorithms for data streams.

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Author information

Authors and Affiliations

  1. University of Waikato, Hamilton, New Zealand

    Albert Bifet & Eibe Frank

Authors
  1. Albert Bifet
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  2. Eibe Frank
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Waikato, Hamilton, New Zealand

    Bernhard Pfahringer

  2. Department of Computer Science, The University of Waikato, Private Bag 3105, 3240, Hamilton, New Zealand

    Geoff Holmes

  3. School of Computer Science and Engineering, The University of New South Wales, 2052, Sydney, Australia

    Achim Hoffmann

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© 2010 Springer-Verlag Berlin Heidelberg

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Bifet, A., Frank, E. (2010). Sentiment Knowledge Discovery in Twitter Streaming Data. In: Pfahringer, B., Holmes, G., Hoffmann, A. (eds) Discovery Science. DS 2010. Lecture Notes in Computer Science(), vol 6332. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16184-1_1

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  • DOI: https://doi.org/10.1007/978-3-642-16184-1_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16183-4

  • Online ISBN: 978-3-642-16184-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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