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News Headline as a Form of News Text Compression

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Social Informatics (SocInfo 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11186))

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Abstract

In this paper we analyze news text collections (clusters) via extracting their paraphrase headlines into a paraphrase graph and working with this graph. Our aim is to test whether news headline is an appropriate form of news text compression. Different types of news collections: dynamic, static and combined (both dynamic and static) clusters are analyzed and it is shown that their respective paraphrase graphs reflect the characteristics of the texts. We also automatically extract the most informationally important linked fragments of news texts, and these fragments characterize news texts as either informative, conveying some information, or publicistic ones, trying to affect the readers emotionally. It is shown that news headlines of the informative type do represent their respective compressed news reports.

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Notes

  1. 1.

    A program implementing the described algorithm is available at http://donelaitis.vdu.lt/~vidas/tools.htm.

  2. 2.

    https://www.yworks.com/products/yed .

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Author information

Authors and Affiliations

  1. National Research University Higher School of Economics, 20 Myasnitskaya ul., Moscow, Russian Federation

    Nataliya Kochetkova

  2. St.-Petersburg State University, 7/9 Universitetskaya Nab., St.-Petersburg, Russian Federation

    Ekaterina Pronoza & Elena Yagunova

Authors
  1. Nataliya Kochetkova
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  2. Ekaterina Pronoza
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  3. Elena Yagunova
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Corresponding author

Correspondence to Ekaterina Pronoza .

Editor information

Editors and Affiliations

  1. University of Koblenz, Koblenz, Germany

    Steffen Staab

  2. National Research University Higher School of Economics, St. Petersburg, Russia

    Olessia Koltsova

  3. National Research University Higher School of Economics, Moscow, Russia

    Dmitry I. Ignatov

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Kochetkova, N., Pronoza, E., Yagunova, E. (2018). News Headline as a Form of News Text Compression. In: Staab, S., Koltsova, O., Ignatov, D. (eds) Social Informatics. SocInfo 2018. Lecture Notes in Computer Science(), vol 11186. Springer, Cham. https://doi.org/10.1007/978-3-030-01159-8_13

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  • DOI: https://doi.org/10.1007/978-3-030-01159-8_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01158-1

  • Online ISBN: 978-3-030-01159-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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