TY - GEN
T1 - Stance Prediction for Russian: Data and Analysis
AU - Lozhnikov, Nikita
AU - Derczynski, Leon
AU - Mazzara, Manuel
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
U2 - 10.1007/978-3-030-14687-0_16
DO - 10.1007/978-3-030-14687-0_16
M3 - Article in proceedings
SN - 978-3-030-14686-3
T3 - Advances in Intelligent Systems and Computing
SP - 176
EP - 186
BT - Proceedings of 6th International Conference in Software Engineering for Defence Applications
PB - Springer
ER -