Stance Prediction for Russian: Data and Analysis

Nikita Lozhnikov, Leon Derczynski, Manuel Mazzara

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review


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.
Original languageEnglish
Title of host publicationProceedings of 6th International Conference in Software Engineering for Defence Applications : SEDA 2018
Publication date2018
ISBN (Print)978-3-030-14686-3
ISBN (Electronic)978-3-030-14687-0
Publication statusPublished - 2018
SeriesAdvances in Intelligent Systems and Computing


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