metadata

annotations_creators:
  - crowdsourced
language_creators:
  - found
language:
  - en
license:
  - cc-by-4.0
multilinguality:
  - monolingual
size_categories:
  - 10K<n<100K
source_datasets: []
task_categories:
  - text-classification
task_ids:
  - fact-checking
pretty_name: RumourEval 2019
tags:
  - stance-detection

Dataset Card for "rumoureval_2019"

Dataset Description
Dataset Structure
Dataset Creation
Considerations for Using the Data
Additional Information

Dataset Description

Homepage: https://competitions.codalab.org/competitions/19938
Repository: https://figshare.com/articles/dataset/RumourEval_2019_data/8845580
Paper: https://aclanthology.org/S19-2147/, https://arxiv.org/abs/1809.06683
Point of Contact: Leon Derczynski
Size of downloaded dataset files:
Size of the generated dataset:
Total amount of disk used:

Dataset Summary

Stance prediction task in English. The goal is to predict whether a given reply to a claim either supports, denies, questions, or simply comments on the claim. Ran as a SemEval task in 2019.

Supported Tasks and Leaderboards

SemEval 2019 task 1

Languages

English of various origins, bcp47: en

Dataset Structure

Data Instances

polstance

An example of 'train' looks as follows.

{
    'id': '0', 
    'source_text': 'Appalled by the attack on Charlie Hebdo in Paris, 10 - probably journalists - now confirmed dead. An attack on free speech everywhere.', 
    'reply_text': '@m33ryg @tnewtondunn @mehdirhasan Of course it is free speech, that\'s the definition of "free speech" to openly make comments or draw a pic!', 
    'label': 3
}

Data Fields

id: a string feature.
source_text: a string expressing a claim/topic.
reply_text: a string to be classified for its stance to the source.
label: a class label representing the stance the text expresses towards the target. Full tagset with indices:

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

quoteID: a string of the internal quote ID.
party: a string describing the party affiliation of the quote utterer at the time of utterance.
politician: a string naming the politician who uttered the quote.

Data Splits

name	instances
train	7 005
dev	2 425
test	2 945

Dataset Creation

Curation Rationale

Source Data

Initial Data Collection and Normalization

Who are the source language producers?

Twitter users

Annotations

Annotation process

Detailed in Analysing How People Orient to and Spread Rumours in Social Media by Looking at Conversational Threads

Who are the annotators?

Personal and Sensitive Information

Considerations for Using the Data

Social Impact of Dataset

Discussion of Biases

Other Known Limitations

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{gorrell-etal-2019-semeval,
    title = "{S}em{E}val-2019 Task 7: {R}umour{E}val, Determining Rumour Veracity and Support for Rumours",
    author = "Gorrell, Genevieve  and
      Kochkina, Elena  and
      Liakata, Maria  and
      Aker, Ahmet  and
      Zubiaga, Arkaitz  and
      Bontcheva, Kalina  and
      Derczynski, Leon",
    booktitle = "Proceedings of the 13th International Workshop on Semantic Evaluation",
    month = jun,
    year = "2019",
    address = "Minneapolis, Minnesota, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/S19-2147",
    doi = "10.18653/v1/S19-2147",
    pages = "845--854",
}

Contributions

Author-added dataset @leondz

Datasets:

strombergnlp
/

rumoureval_2019