Stance Prediction for Russian: Data and Analysis

Nikita Lozhnikov, Leon Derczynski, Manuel Mazzara
9/5/2018
cs.CL

Official code: nikitml/rustance (6 stars, last commit 2018-09-05).

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.

View on arXivView PDF

Code Implementations(1)

nikitml/rustanceOfficial100%

RuStance. Russian Stance Classification: Data and Analysis.

62Apr 7, 20188 years ago

Similar Papers

Stance Detection with Collaborative Role-Infused LLM-Based Agents

90% match1 repo112023

A Retrospective Analysis of the Fake News Challenge Stance Detection Task

87% match2 repos472018

Chain-of-Thought Embeddings for Stance Detection on Social Media

87% match2023

Guiding Computational Stance Detection with Expanded Stance Triangle Framework

87% match2023

Combining Similarity Features and Deep Representation Learning for Stance Detection in the Context of Checking Fake News

87% match1 repo132018

Can We Identify Stance Without Target Arguments? A Study for Rumour Stance Classification

87% match2023

Cite this paper

@article{lozhnikov2018stance,
  title  = {Stance Prediction for Russian: Data and Analysis},
  author = {Nikita Lozhnikov and Leon Derczynski and Manuel Mazzara},
  year   = {2018},
  eprint = {1809.01574},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/1809.01574}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/1809.01574.svg)](https://codeofpaper.com/paper/1809.01574)

Discussion