Dataset Card for "rustance"

Dataset Summary

This is a stance prediction dataset in Russian. The dataset contains comments on news articles, and rows are a comment, the title of the news article it responds to, and the stance of the comment towards the article.

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.

Supported Tasks and Leaderboards

• Stance Detection: Stance Detection on RuStance

Languages

Russian, as spoken on the Meduza website (i.e. from multiple countries) (bcp47:ru)

Dataset Structure

Data Instances

rustance

• Size of downloaded dataset files: 349.79 KiB
• Size of the generated dataset: 366.11 KiB
• Total amount of disk used: 715.90 KiB

An example of 'train' looks as follows.

{
  'id': '0', 
  'text': 'Волки, волки!!', 
  'title': 'Минобороны обвинило «гражданского сотрудника» в публикации скриншота из игры вместо фото террористов. И показало новое «неоспоримое подтверждение»', 
  'stance': 3
}

Data Fields

• id: a string feature.
• text: a string expressing a stance.
• title: a string of the target/topic annotated here.
• stance: a class label representing the stance the text expresses towards the target. Full tagset with indices:

                            0: "support",
                            1: "deny",
                            2: "query",
                            3: "comment",

Data Splits

name	train
rustance	958 sentences

Dataset Creation

Curation Rationale

Toy data for training and especially evaluating stance prediction in Russian

Source Data

Initial Data Collection and Normalization

The data is comments scraped from a Russian news site not situated in Russia, Meduza, in 2018.

Who are the source language producers?

Russian speakers including from the Russian diaspora, especially Latvia

Annotations

Annotation process

Annotators labelled comments for supporting, denying, querying or just commenting on a news article.

Who are the annotators?

Russian native speakers, IT education, male, 20s.

Personal and Sensitive Information

The data was public at the time of collection. No PII removal has been performed.

Considerations for Using the Data

Social Impact of Dataset

There's a risk of misinformative content being in this data. The data has NOT been vetted for any content.

Discussion of Biases

Other Known Limitations

The above limitations apply.

Additional Information

Dataset Curators

The dataset is curated by the paper's authors.

Licensing Information

The authors distribute this data under Creative Commons attribution license, CC-BY 4.0.

Citation Information

@inproceedings{lozhnikov2018stance,
  title={Stance prediction for russian: data and analysis},
  author={Lozhnikov, Nikita and Derczynski, Leon and Mazzara, Manuel},
  booktitle={International Conference in Software Engineering for Defence Applications},
  pages={176--186},
  year={2018},
  organization={Springer}
}

Contributions

Author-added dataset @leondz