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International Conference on Web Engineering

ICWE 2012: Web Engineering pp 153–168Cite as

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Twinder: A Search Engine for Twitter Streams

Twinder: A Search Engine for Twitter Streams

  • Ke Tao19,
  • Fabian Abel19,
  • Claudia Hauff19 &
  • …
  • Geert-Jan Houben19 
  • Conference paper
  • 2326 Accesses

  • 17 Citations

Part of the Lecture Notes in Computer Science book series (LNISA,volume 7387)

Abstract

How can one effectively identify relevant messages in the hundreds of millions of Twitter messages that are posted every day? In this paper, we aim to answer this fundamental research question and introduce Twinder, a scalable search engine for Twitter streams. The Twinder search engine exploits various features to estimate the relevance of Twitter messages (tweets) for a given topic. Among these features are both topic-sensitive features such as measures that compute the semantic relatedness between a tweet and a topic as well as topic-insensitive features which characterize a tweet with respect to its syntactical, semantic, sentiment and contextual properties. In our evaluations, we investigate the impact of the different features on retrieval performance. Our results prove the effectiveness of the Twinder search engine - we show that in particular semantic features yield high precision and recall values of more than 35% and 45% respectively.

Keywords

  • Contextual Feature
  • Twitter User
  • Relevance Estimation
  • Negative Sentiment
  • Twitter Message

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Author information

Authors and Affiliations

  1. Web Information Systems, Delft University of Technology, The Netherlands

    Ke Tao, Fabian Abel, Claudia Hauff & Geert-Jan Houben

Authors
  1. Ke Tao
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  2. Fabian Abel
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  3. Claudia Hauff
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  4. Geert-Jan Houben
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Editor information

Editors and Affiliations

  1. Dipartimento di Elettronica e Informazione, Politecnico di Milano, Via Ponzio 34/5, 20133, Milano, Italy

    Marco Brambilla

  2. Department of Computer Science, Tokyo Institute of Technology, 2-12-1 Oookayama, 152-8552, Tokyo, Japan

    Takehiro Tokuda

  3. Institut für Informatik, Freie Universität Berlin, Königin-Luise-Strasse 24-26, 14195, Berlin, Germany

    Robert Tolksdorf

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© 2012 Springer-Verlag Berlin Heidelberg

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Cite this paper

Tao, K., Abel, F., Hauff, C., Houben, GJ. (2012). Twinder: A Search Engine for Twitter Streams. In: Brambilla, M., Tokuda, T., Tolksdorf, R. (eds) Web Engineering. ICWE 2012. Lecture Notes in Computer Science, vol 7387. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31753-8_11

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  • DOI: https://doi.org/10.1007/978-3-642-31753-8_11

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  • Print ISBN: 978-3-642-31752-1

  • Online ISBN: 978-3-642-31753-8

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