Datasets:
Tasks:
Text Classification
Modalities:
Text
Sub-tasks:
fact-checking
Languages:
English
Size:
1K - 10K
ArXiv:
Tags:
stance-detection
License:
| annotations_creators: | |
| - crowdsourced | |
| language_creators: | |
| - found | |
| language: | |
| - en | |
| license: | |
| - cc-by-4.0 | |
| multilinguality: | |
| - monolingual | |
| pretty_name: RumourEval 2019 | |
| size_categories: | |
| - 10K<n<100K | |
| source_datasets: [] | |
| task_categories: | |
| - text-classification | |
| task_ids: | |
| - fact-checking | |
| - text-classification-other-stance-detection | |
| # Dataset Card for "rumoureval_2019" | |
| ## Table of Contents | |
| - [Dataset Description](#dataset-description) | |
| - [Dataset Summary](#dataset-summary) | |
| - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) | |
| - [Languages](#languages) | |
| - [Dataset Structure](#dataset-structure) | |
| - [Data Instances](#data-instances) | |
| - [Data Fields](#data-fields) | |
| - [Data Splits](#data-splits) | |
| - [Dataset Creation](#dataset-creation) | |
| - [Curation Rationale](#curation-rationale) | |
| - [Source Data](#source-data) | |
| - [Annotations](#annotations) | |
| - [Personal and Sensitive Information](#personal-and-sensitive-information) | |
| - [Considerations for Using the Data](#considerations-for-using-the-data) | |
| - [Social Impact of Dataset](#social-impact-of-dataset) | |
| - [Discussion of Biases](#discussion-of-biases) | |
| - [Other Known Limitations](#other-known-limitations) | |
| - [Additional Information](#additional-information) | |
| - [Dataset Curators](#dataset-curators) | |
| - [Licensing Information](#licensing-information) | |
| - [Citation Information](#citation-information) | |
| - [Contributions](#contributions) | |
| ## Dataset Description | |
| - **Homepage:** [https://competitions.codalab.org/competitions/19938](https://competitions.codalab.org/competitions/19938) | |
| - **Repository:** [https://figshare.com/articles/dataset/RumourEval_2019_data/8845580](https://figshare.com/articles/dataset/RumourEval_2019_data/8845580) | |
| - **Paper:** [https://aclanthology.org/S19-2147/](https://aclanthology.org/S19-2147/), [https://arxiv.org/abs/1809.06683](https://arxiv.org/abs/1809.06683) | |
| - **Point of Contact:** [Leon Derczynski](https://github.com/leondz) | |
| - **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](https://journals.plos.org/plosone/article/authors?id=10.1371/journal.pone.0150989) | |
| #### 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](https://github.com/leondz) | |