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Stance Prediction for Russian: Data and Analysis

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Proceedings of 6th International Conference in Software Engineering for Defence Applications (SEDA 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 925))

Abstract

Stance detection is a critical component of rumour and fake news identification. It involves the extraction of the stance a particular author takes related to a given claim, both expressed in text. This paper investigates stance classification for Russian. It introduces a new dataset, RuStance, of Russian tweets and news comments from multiple sources, covering multiple stories, as well as text classification approaches to stance detection as benchmarks over this data in this language. As well as presenting this openly-available dataset, the first of its kind for Russian, the paper presents a baseline for stance prediction in the language.

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Author information

Authors and Affiliations

  1. Innopolis University, Innopolis, Russian Federation

    Nikita Lozhnikov & Manuel Mazzara

  2. ITU Copenhagen, Copenhagen, Denmark

    Leon Derczynski

Authors
  1. Nikita Lozhnikov
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  2. Leon Derczynski
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  3. Manuel Mazzara
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Corresponding authors

Correspondence to Nikita Lozhnikov , Leon Derczynski or Manuel Mazzara .

Editor information

Editors and Affiliations

  1. University of Bologna, Bologna, Italy

    Paolo Ciancarini

  2. Innopolis University, Innopolis, Russia

    Manuel Mazzara

  3. Innopolis University, Innopolis, Russia

    Angelo Messina

  4. Innopolis University, Innopolis, Russia

    Alberto Sillitti

  5. Innopolis University, Innopolis, Russia

    Giancarlo Succi

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Lozhnikov, N., Derczynski, L., Mazzara, M. (2020). Stance Prediction for Russian: Data and Analysis. In: Ciancarini, P., Mazzara, M., Messina, A., Sillitti, A., Succi, G. (eds) Proceedings of 6th International Conference in Software Engineering for Defence Applications. SEDA 2018. Advances in Intelligent Systems and Computing, vol 925. Springer, Cham. https://doi.org/10.1007/978-3-030-14687-0_16

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