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+ # Dataset Card for Bernice Pre-train Data
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+
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+ ## Table of Contents
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+ - [Table of Contents](#table-of-contents)
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+ - [Dataset Description](#dataset-description)
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+ - [Dataset Summary](#dataset-summary)
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+ - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
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+ - [Languages](#languages)
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+ - [Dataset Structure](#dataset-structure)
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+ - [Data Instances](#data-instances)
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+ - [Data Fields](#data-fields)
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+ - [Data Splits](#data-splits)
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+ - [Dataset Creation](#dataset-creation)
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+ - [Curation Rationale](#curation-rationale)
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+ - [Source Data](#source-data)
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+ - [Annotations](#annotations)
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+ - [Personal and Sensitive Information](#personal-and-sensitive-information)
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+ - [Considerations for Using the Data](#considerations-for-using-the-data)
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+ - [Social Impact of Dataset](#social-impact-of-dataset)
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+ - [Discussion of Biases](#discussion-of-biases)
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+ - [Other Known Limitations](#other-known-limitations)
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+ - [Additional Information](#additional-information)
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+ - [Dataset Curators](#dataset-curators)
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+ - [Licensing Information](#licensing-information)
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+ - [Citation Information](#citation-information)
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+ - [Contributions](#contributions)
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+
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+ ## Dataset Description
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+
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+ - **Homepage:** N/A
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+ - **Repository:** https://github.com/JHU-CLSP/Bernice-Twitter-encoder
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+ - **Paper:** _Bernice: A Multilingual Pre-trained Encoder for Twitter_ at [EMNLP 2022](https://preview.aclanthology.org/emnlp-22-ingestion/2022.emnlp-main.415)
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+ - **Leaderboard:** N/A
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+ - **Point of Contact:** Alexandra DeLucia aadelucia (at) jhu.edu
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+
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+ ### Dataset Summary
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+
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+ Tweet IDs for the 2.5 billion multilingual tweets used to train Bernice, a Twitter encoder.
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+ The tweets are from the public 1% Twitter API stream from January 2016 to December 2021.
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+ 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.
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+ Tweets need to be re-gathered via the Twitter API. We suggest [Hydrator](https://github.com/DocNow/hydrator) or [tweepy](https://www.tweepy.org/).
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+
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+
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+ ### Supported Tasks and Leaderboards
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+
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+ N/A
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+
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+ ### Languages
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+
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+ 65 languages (ISO 639 codes shown below), plus an `und` (undefined) category.
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+ All language identification provided by Twitter API.
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+
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+ | | | | | | | |
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+ |----|-----|----|----|----|-----|----|
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+ | en | ru | ht | zh | bn | ps | lt |
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+ | es | bo | ur | ta | sr | ckb | km |
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+ | pt | it | sv | ro | bg | si | dv |
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+ | ja | th | ca | no | mr | hy | lo |
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+ | ar | de | el | uk | ml | or | ug |
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+ | in | hi | fi | cy | is | pa | |
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+ | ko | pl | cs | ne | te | am | |
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+ | tr | nl | iw | hu | gu | sd | |
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+ | fr | fa | da | eu | kn | my | |
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+ | tl | et | vi | sl | lv | ka | |
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+
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+ ## Dataset Structure
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+
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+ ### Data Instances
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+
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+ [More Information Needed]
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+
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+ ### Data Fields
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+
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+ [More Information Needed]
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+
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+ ### Data Splits
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+
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+ [More Information Needed]
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+
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+
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+ ## Dataset Creation
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+
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+ ### Curation Rationale
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+
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+ Data was gathered to support the training of Bernice, a multilingual pre-trained Twitter encoder.
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+
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+ ### Source Data
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+
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+ #### Initial Data Collection and Normalization
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+
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+ Data was gathered via the Twitter API public 1% stream from January 2016 through December 2021.
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+ Tweets with less than three non-username or URL space-delimited words were removed.
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+ All usernames and URLs were replaced with `@USER` and `HTTPURL`, respectively.
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+
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+ #### Who are the source language producers?
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+
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+ Data was produced by users on Twitter.
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+
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+ ### Annotations
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+
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+ N/A
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+
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+ ### Personal and Sensitive Information
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+
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+ As per Twitter guidelines, only tweet IDs and not full tweets are shared.
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+ 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.
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+
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+ ## Considerations for Using the Data
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+
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+ ### Social Impact of Dataset
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+
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+ [More Information Needed]
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+
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+ ### Discussion of Biases
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+
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+ [More Information Needed]
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+
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+ ### Other Known Limitations
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+
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+ [More Information Needed]
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+
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+
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+ ## Additional Information
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+
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+ ### Dataset Curators
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+
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+ Dataset gathered and processed by Mark Dredze, Alexandra DeLucia, Shijie Wu, Aaron Mueller, Carlos Aguirre, and Philip Resnik.
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+
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+ ### Licensing Information
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+
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+ [More Information Needed]
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+
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+ ### Citation Information
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+
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+ Please cite the Bernice paper if you use this dataset:
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+
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+ > 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.
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+
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+ ### Contributions
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+
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+ Dataset uploaded by [@AADeLucia](https://github.com/AADeLucia).