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Dataset Open Access

A large-scale COVID-19 Twitter chatter dataset for open scientific research - an international collaboration

Banda, Juan M.; Tekumalla, Ramya; Wang, Guanyu; Yu, Jingyuan; Liu, Tuo; Ding, Yuning; Artemova, Katya; Tutubalina, Elena; Chowell, Gerardo

Version 41 of the dataset. 

Due to the relevance of the COVID-19 global pandemic, we are releasing our dataset of tweets acquired from the Twitter Stream related to COVID-19 chatter. Since our first release we have received additional data from our new collaborators, allowing this resource to grow to its current size. Dedicated data gathering started from March 11th yielding over 4 million tweets a day. We have added additional data provided by our new collaborators from January 27th to March 27th, to provide extra longitudinal coverage. Version 10 added ~1.5 million tweets in the Russian language collected between January 1st and May 8th, gracefully provided to us by: Katya Artemova (NRU HSE) and Elena Tutubalina (KFU). From version 12 we have included daily hashtags, mentions and emoijis and their frequencies the respective zip files. From version 14 we have included the tweet identifiers and their respective language for the clean version of the dataset. Since version 20 we have included language and place location for all tweets.

The data collected from the stream captures all languages, but the higher prevalence are:  English, Spanish, and French. We release all tweets and retweets on the full_dataset.tsv file (866,264,887 unique tweets), and a cleaned version with no retweets on the full_dataset-clean.tsv file (216,479,092 unique tweets). There are several practical reasons for us to leave the retweets, tracing important tweets and their dissemination is one of them. For NLP tasks we provide the top 1000 frequent terms in frequent_terms.csv, the top 1000 bigrams in frequent_bigrams.csv, and the top 1000 trigrams in frequent_trigrams.csv. Some general statistics per day are included for both datasets in the full_dataset-statistics.tsv and full_dataset-clean-statistics.tsv files. For more statistics and some visualizations visit: http://www.panacealab.org/covid19/ 

More details can be found (and will be updated faster at: https://github.com/thepanacealab/covid19_twitter) and our pre-print about the dataset (https://arxiv.org/abs/2004.03688

As always, the tweets distributed here are only tweet identifiers (with date and time added) due to the terms and conditions of Twitter to re-distribute Twitter data ONLY for research purposes. They need to be hydrated to be used.

This dataset will be updated bi-weekly at least with additional tweets, look at the github repo for these updates. Release: We have standardized the name of the resource to match our pre-print manuscript and to not have to update it every week.
Files (9.5 GB)
Name Size
emojis.zip
md5:9c73c8dfe31fd3bf9aa8afee8d16c995
5.8 MB Download
frequent_bigrams.csv
md5:0a70fcea7d1df587a60c510addbfdef6
18.5 kB Download
frequent_terms.csv
md5:24c872c1c22dbe5045baac7e89a217a7
11.9 kB Download
frequent_trigrams.csv
md5:e7a418067c571bfb5cddde3d5ad8c40c
24.7 kB Download
full_dataset-statistics.tsv
md5:fa1d390796927c89dc121a0716e1ecc0
6.6 kB Download
full_dataset.tsv.gz
md5:8528c687069e147ed3c863b48267430b
7.2 GB Download
full_dataset_clean-statistics.tsv
md5:954dac15d4b270b8571cbc8adaea0f9f
6.3 kB Download
full_dataset_clean.tsv.gz
md5:c2bc26b797cb5988e3ccd599b0ed6770
2.0 GB Download
hashtags.zip
md5:67381780b199db254fefc4fc8e53173f
116.1 MB Download
mentions.zip
md5:0255d30b6532d338c7fc045474c664c1
192.8 MB Download
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Views 51,449501
Downloads 59,523194
Data volume 71.7 TB216.2 GB
Unique views 39,444422
Unique downloads 15,926115

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