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Sentiment Attitudes and Their Extraction from Analytical Texts

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Text, Speech, and Dialogue (TSD 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11107))

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Abstract

In this paper we study the task of extracting sentiment attitudes from analytical texts. We experiment with the RuSentRel corpus containing annotated Russian analytical texts in the sphere of international relations. Each document in the corpus is annotated with sentiments from the author to mentioned named entities, and attitudes between mentioned entities. We consider the problem of extracting sentiment relations between entities for the whole documents as a three-class machine learning task.

The work is supported by the Russian Foundation for Basic Research (project 16-29-09606).

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Notes

  1. 1.

    https://tac.nist.gov/2014/KBP/Sentiment/index.html.

  2. 2.

    https://github.com/nicolay-r/RuSentRel/tree/v1.0.

  3. 3.

    https://miem.hse.ru/clschool/results.

  4. 4.

    http://scikit-learn.org/stable/.

  5. 5.

    http://rusvectores.org/.

  6. 6.

    http://www.labinform.ru/pub/rusentilex/index.htm.

  7. 7.

    https://github.com/nicolay-r/sentiment-relation-classifiers/tree/tsd_2018.

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Author information

Authors and Affiliations

  1. Bauman Moscow State Technical University, Moscow, Russia

    Nicolay Rusnachenko

  2. Lomonosov Moscow State University, Moscow, Russia

    Natalia Loukachevitch

Authors
  1. Nicolay Rusnachenko
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  2. Natalia Loukachevitch
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Corresponding authors

Correspondence to Nicolay Rusnachenko or Natalia Loukachevitch .

Editor information

Editors and Affiliations

  1. Faculty of Informatics, Masaryk University, Brno, Czech Republic

    Petr Sojka

  2. Faculty of Informatics, Masaryk University, Brno, Czech Republic

    Aleš Horák

  3. Faculty of Informatics, Masaryk University, Brno, Czech Republic

    Ivan Kopeček

  4. Faculty of Informatics, Masaryk University, Brno, Czech Republic

    Karel Pala

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Rusnachenko, N., Loukachevitch, N. (2018). Sentiment Attitudes and Their Extraction from Analytical Texts. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech, and Dialogue. TSD 2018. Lecture Notes in Computer Science(), vol 11107. Springer, Cham. https://doi.org/10.1007/978-3-030-00794-2_4

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  • DOI: https://doi.org/10.1007/978-3-030-00794-2_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00793-5

  • Online ISBN: 978-3-030-00794-2

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