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International Conference on Theory and Practice of Digital Libraries

TPDL 2015: Research and Advanced Technology for Digital Libraries pp 364–367Cite as

Extracting a Topic Specific Dataset from a Twitter Archive

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9316))

Abstract

Datasets extracted from the microblogging service Twitter are often generated using specific query terms or hashtags. We describe how a dataset produced using the query term ‘syria’ can be increased in size to include tweets on the topic of Syria that do not contain that query term. We compare three methods for this task, using the top hashtags from the set as search terms, using a hand selected set of hashtags as search terms and using LDA topic modelling to cluster tweets and selecting appropriate clusters. We describe an evaluation method for accessing the relevance and accuracy of the tweets returned.

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Author information

Authors and Affiliations

  1. School of Informatics, University of Edinburgh, Edinburgh, UK

    Clare Llewellyn, Claire Grover, Beatrice Alex, Jon Oberlander & Richard Tobin

Authors
  1. Clare Llewellyn
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  2. Claire Grover
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  3. Beatrice Alex
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  4. Jon Oberlander
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  5. Richard Tobin
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Corresponding author

Correspondence to Clare Llewellyn .

Editor information

Editors and Affiliations

  1. Ionian University, Corfu, Greece

    Sarantos Kapidakis

  2. Poznań Supercomputing and Networking Center, Poznań, Poland

    Cezary Mazurek

  3. Networking Center, Poznań Supercomputing and, Poznań, Poland

    Marcin Werla

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© 2015 Springer International Publishing Switzerland

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Cite this paper

Llewellyn, C., Grover, C., Alex, B., Oberlander, J., Tobin, R. (2015). Extracting a Topic Specific Dataset from a Twitter Archive. In: Kapidakis, S., Mazurek, C., Werla, M. (eds) Research and Advanced Technology for Digital Libraries. TPDL 2015. Lecture Notes in Computer Science(), vol 9316. Springer, Cham. https://doi.org/10.1007/978-3-319-24592-8_36

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  • DOI: https://doi.org/10.1007/978-3-319-24592-8_36

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24591-1

  • Online ISBN: 978-3-319-24592-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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