Datasets:
Tasks:
Other
Multilinguality:
multilingual
Size Categories:
1B<n<10B
Language Creators:
found
Annotations Creators:
no-annotation
Source Datasets:
original
License:
| annotations_creators: | |
| - no-annotation | |
| language: | |
| - en | |
| - es | |
| - pt | |
| - ja | |
| - ar | |
| - in | |
| - ko | |
| - tr | |
| - fr | |
| - tl | |
| - ru | |
| - it | |
| - th | |
| - de | |
| - hi | |
| - pl | |
| - nl | |
| - fa | |
| - et | |
| - ht | |
| - ur | |
| - sv | |
| - ca | |
| - el | |
| - fi | |
| - cs | |
| - iw | |
| - da | |
| - vi | |
| - zh | |
| - ta | |
| - ro | |
| - no | |
| - uk | |
| - cy | |
| - ne | |
| - hu | |
| - eu | |
| - sl | |
| - lv | |
| - lt | |
| - bn | |
| - sr | |
| - bg | |
| - mr | |
| - ml | |
| - is | |
| - te | |
| - gu | |
| - kn | |
| - ps | |
| - ckb | |
| - si | |
| - hy | |
| - or | |
| - pa | |
| - am | |
| - sd | |
| - my | |
| - ka | |
| - km | |
| - dv | |
| - lo | |
| - ug | |
| - bo | |
| language_creators: | |
| - found | |
| license: | |
| - mit | |
| multilinguality: | |
| - multilingual | |
| pretty_name: Bernice Pretrain Data | |
| size_categories: | |
| - 1B<n<10B | |
| source_datasets: | |
| - original | |
| tags: | |
| - slang | |
| - code switch | |
| - social | |
| - social media | |
| task_categories: | |
| - other | |
| task_ids: [] | |
| # Dataset Card for Bernice Pre-train Data | |
| ## Table of Contents | |
| - [Table of Contents](#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:** N/A | |
| - **Repository:** https://github.com/JHU-CLSP/Bernice-Twitter-encoder | |
| - **Paper:** _Bernice: A Multilingual Pre-trained Encoder for Twitter_ at [EMNLP 2022](https://preview.aclanthology.org/emnlp-22-ingestion/2022.emnlp-main.415) | |
| - **Leaderboard:** N/A | |
| - **Point of Contact:** Alexandra DeLucia aadelucia (at) jhu.edu | |
| ### Dataset Summary | |
| Tweet IDs for the 2.5 billion multilingual tweets used to train Bernice, a Twitter encoder. | |
| Read the paper [here](https://preview.aclanthology.org/emnlp-22-ingestion/2022.emnlp-main.415). | |
| The tweets are from the public 1% Twitter API stream from January 2016 to December 2021. | |
| Twitter-provided language metadata is provided with the tweet ID. The data contains 66 unique languages, as identified by [ISO 639 language codes](https://www.wikiwand.com/en/List_of_ISO_639-1_codes), including `und` for undefined languages. | |
| Tweets need to be re-gathered via the Twitter API. We suggest [Hydrator](https://github.com/DocNow/hydrator) or [tweepy](https://www.tweepy.org/). | |
| To load with HuggingFace: | |
| ```python | |
| from datasets import load_dataset | |
| dataset = load_dataset("jhu-clsp/bernice-pretrain-data") | |
| for i, row in enumerate(dataset["train"]): | |
| print(row) | |
| if i > 10: | |
| break | |
| ``` | |
| If you only want Indic languages, use | |
| ```python | |
| dataset = load_dataset("jhu-clsp/bernice-pretrain-data", "indic") | |
| ``` | |
| ### Supported Tasks and Leaderboards | |
| N/A | |
| ### Languages | |
| 65 languages (ISO 639 codes shown below), plus an `und` (undefined) category. | |
| All language identification provided by Twitter API. | |
| | | | | | | | | | |
| |----|-----|----|----|----|-----|----| | |
| | en | ru | ht | zh | bn | ps | lt | | |
| | es | bo | ur | ta | sr | ckb | km | | |
| | pt | it | sv | ro | bg | si | dv | | |
| | ja | th | ca | no | mr | hy | lo | | |
| | ar | de | el | uk | ml | or | ug | | |
| | in | hi | fi | cy | is | pa | | | |
| | ko | pl | cs | ne | te | am | | | |
| | tr | nl | iw | hu | gu | sd | | | |
| | fr | fa | da | eu | kn | my | | | |
| | tl | et | vi | sl | lv | ka | | | |
| ## Dataset Structure | |
| ### Data Instances | |
| Data is provided in gzip'd files organized by year and month of tweet origin. | |
| Tweets are one per line, with fields separated by tabs. | |
| ### Data Fields | |
| * `tweet ID`: ID of tweet | |
| * `lang`: ISO 639 code of language, provided by Twitter metadata. Accuracy of label is not known. | |
| * `year`: Year tweet was created. Year is also provided in the file names. | |
| ### Data Splits | |
| [More Information Needed] | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| Data was gathered to support the training of Bernice, a multilingual pre-trained Twitter encoder. | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| Data was gathered via the Twitter API public 1% stream from January 2016 through December 2021. | |
| Tweets with less than three non-username or URL space-delimited words were removed. | |
| All usernames and URLs were replaced with `@USER` and `HTTPURL`, respectively. | |
| #### Who are the source language producers? | |
| Data was produced by users on Twitter. | |
| ### Annotations | |
| N/A | |
| ### Personal and Sensitive Information | |
| As per Twitter guidelines, only tweet IDs and not full tweets are shared. | |
| Tweets will only be accessible if user has not removed their account (or been banned), tweets were deleted or removed, or a user changed their account access to private. | |
| ## Considerations for Using the Data | |
| ### Social Impact of Dataset | |
| [More Information Needed] | |
| ### Discussion of Biases | |
| [More Information Needed] | |
| ### Other Known Limitations | |
| [More Information Needed] | |
| ## Additional Information | |
| ### Dataset Curators | |
| Dataset gathered and processed by Mark Dredze, Alexandra DeLucia, Shijie Wu, Aaron Mueller, Carlos Aguirre, and Philip Resnik. | |
| ### Licensing Information | |
| MIT | |
| ### Citation Information | |
| Please cite the Bernice paper if you use this dataset: | |
| > Alexandra DeLucia, Shijie Wu, Aaron Mueller, Carlos Aguirre, Philip Resnik, and Mark Dredze. 2022. Bernice: A Multilingual Pre-trained Encoder for Twitter. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 6191–6205, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics. | |
| ### Contributions | |
| Dataset uploaded by [@AADeLucia](https://github.com/AADeLucia). | |