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Exploring the Meaning behind Twitter Hashtags through Clustering

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Business Information Systems Workshops (BIS 2012)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 127))

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Abstract

Social networks are generators of large amount of data produced by users, who are not limited with respect to the content of the information they exchange. The data generated can be a good indicator of trends and topic preferences among users. In our paper we focus on analyzing and representing hashtags by the corpus in which they appear. We cluster a large set of hashtags using K-means on map reduce in order to process data in a distributed manner. Our intention is to retrieve connections that might exist between different hashtags and their textual representation, and grasp their semantics through the main topics they occur with.

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Author information

Authors and Affiliations

  1. Faculty of Economics and Business Administration, Babes-Bolyai University, Cluj-Napoca, Romania

    Cristina Ioana Muntean, Gabriela Andreea Morar & Darie Moldovan

Authors
  1. Cristina Ioana Muntean
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  2. Gabriela Andreea Morar
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  3. Darie Moldovan
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Editor information

Editors and Affiliations

  1. Poznań University of Economics, Poznań, Poland

    Witold Abramowicz

  2. Knowledge Media Institute, The Open University, Walton Hall, MK7 6AA, Milton Keynes, UK

    John Domingue

  3. Poznań University of Economics, Al. Niepodległości 10, 60-967, Poznań, Poland

    Krzysztof Węcel

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© 2012 Springer-Verlag Berlin Heidelberg

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Muntean, C.I., Morar, G.A., Moldovan, D. (2012). Exploring the Meaning behind Twitter Hashtags through Clustering. In: Abramowicz, W., Domingue, J., Węcel, K. (eds) Business Information Systems Workshops. BIS 2012. Lecture Notes in Business Information Processing, vol 127. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34228-8_22

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  • DOI: https://doi.org/10.1007/978-3-642-34228-8_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34227-1

  • Online ISBN: 978-3-642-34228-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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