Stance Prediction for Russian: Data and Analysis
- Nikita Lozhnikov,
- ,
- Manuel Mazzara
- Innopolis University,
- ,
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewOpen access
Publication Information
Output type
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewHost publication Subtitle
SEDA 2018Original language
EnglishPages from-to (Number of pages)
Pages 176-186Publication milestones
- Published - 2018
Publication status
Published - 2018
Publisher
Springer, United States, GermanyBook series
- Book series name: Advances in Intelligent Systems and Computing
Volume: 925
ISSN: 2194-5357
ISBN (Print)
978-3-030-14686-3ISBN (Electronic)
978-3-030-14687-0Publication IDs
- Scopus: 85064183861
Host publication title
Proceedings of 6th International Conference in Software Engineering for Defence ApplicationsAbstract
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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