added paper link to summary
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README.md
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### Dataset Summary
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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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### Dataset Summary
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Tweet IDs for the 2.5 billion multilingual tweets used to train Bernice, a Twitter encoder.
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Read the paper [here](https://preview.aclanthology.org/emnlp-22-ingestion/2022.emnlp-main.415).
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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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