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Political Hashtag Trends

  • Conference paper
Advances in Information Retrieval (ECIR 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7814))

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Abstract

Political Hashtag Trends (PHT) is an analysis tool for political left-vs.-right polarization of Twitter hashtags. PHT computes a leaning for trending, political hashtags in a given week, giving insights into the polarizing U.S. American issues on Twitter. The leaning of a hashtag is derived in two steps. First, users retweeting a set of “seed users” with a known political leaning, such as Barack Obama or Mitt Romney, are identified and the corresponding leaning is assigned to retweeters. Second, a hashtag is assigned a fractional leaning corresponding to which retweeting users used it. Non-political hashtags are removed by requiring certain hashtag co-occurrence patterns. PHT also offers functionality to put the results into context. For example, it shows example tweets from different leanings, it shows historic information and it links to the New York Times archives to explore a topic in depth. In this paper, we describe the underlying methodology and the functionality of the demo.

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References

  1. Weber, I., Garimella, V.R.K., Borra, E.: Mining web query logs to analyze political issues. In: WebSci, pp. 330–339 (2012)

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  2. Subasic, I., Castillo, C.: The effects of query bursts on web search. In: WI, pp. 374–381 (2010)

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  3. Weber, I., Garimella, V.R.K., Borra, E.: Political search trends. In: SIGIR, p. 1012 (2012)

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Author information

Authors and Affiliations

  1. Qatar Computing Research Institute, Doha, Qatar

    Ingmar Weber & Venkata Rama Kiran Garimella

  2. L3S, Hanover, Germany

    Asmelash Teka

Authors
  1. Ingmar Weber
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  2. Venkata Rama Kiran Garimella
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  3. Asmelash Teka
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Editor information

Editors and Affiliations

  1. Yandex, Leo Tolstoy, 16, 119021, Moscow, Russia

    Pavel Serdyukov  & Ilya Segalovich  & 

  2. Kontur Labs and Ural Federal University, Fonvizina 3-27, 620078, Yekaterinburg, Russia

    Pavel Braslavski

  3. National Research University Higher School of Economics (HSE), Pokrovskii bd 11, 109028, Moscow, Russia

    Sergei O. Kuznetsov

  4. University of Amsterdam, Turfdraagsterpad 9, 1012 XT, Amsterdam, The Netherlands

    Jaap Kamps

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

    Stefan Rüger

  6. Mathematics & Computer Science Department, Emory University, 400 dowman Drive, 30329, Atlanta, GA, USA

    Eugene Agichtein

  7. Department of Computer Science, University College London, Gower Street, WC1E 6BT, London, UK

    Emine Yilmaz

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© 2013 Springer-Verlag Berlin Heidelberg

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Weber, I., Garimella, V.R.K., Teka, A. (2013). Political Hashtag Trends. In: Serdyukov, P., et al. Advances in Information Retrieval. ECIR 2013. Lecture Notes in Computer Science, vol 7814. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36973-5_102

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  • DOI: https://doi.org/10.1007/978-3-642-36973-5_102

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-36972-8

  • Online ISBN: 978-3-642-36973-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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