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International Conference on Web Engineering

ICWE 2012: Web Engineering pp 16–30Cite as

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News-Topic Oriented Hashtag Recommendation in Twitter Based on Characteristic Co-occurrence Word Detection

News-Topic Oriented Hashtag Recommendation in Twitter Based on Characteristic Co-occurrence Word Detection

  • Feng Xiao19,
  • Tomoya Noro19 &
  • Takehiro Tokuda19 
  • Conference paper
  • 2500 Accesses

  • 16 Citations

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

Abstract

Hashtags, which started to be widely used since 2007, are always utilized to mark keywords in tweets to categorize messages and form conversation for topics in Twitter. However, it is hard for users to use hashtags for sharing their opinions/interests/comments for their interesting topics. In this paper, we present a new approach for recommending news-topic oriented hashtags to help Twitter users easily join the conversation about news topics in Twitter. We first detect topic-specific informative words co-occurring with a given target word, which we call characteristic co-occurrence words, from news articles to form a vector for representing the news topic. Then by creating a hashtag vector based on tweets with the same hashtag, we calculate the similarity between these two vectors and recommend hashtags of high similarity scores with the news topic. Experimental results show that our approach could recommend hashtags which are highly relevant to the news topics, helping users share their tweets with others in Twitter.

Keywords

  • Social Media
  • hashtags
  • tweet
  • characteristic co-occurrence word
  • clustering
  • news topic
  • Twitter

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Author information

Authors and Affiliations

  1. Department of Computer Science, Tokyo Institute of Technology, Meguro, Tokyo, 152-8552, Japan

    Feng Xiao, Tomoya Noro & Takehiro Tokuda

Authors
  1. Feng Xiao
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  2. Tomoya Noro
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  3. Takehiro Tokuda
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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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Xiao, F., Noro, T., Tokuda, T. (2012). News-Topic Oriented Hashtag Recommendation in Twitter Based on Characteristic Co-occurrence Word Detection. 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_2

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  • DOI: https://doi.org/10.1007/978-3-642-31753-8_2

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