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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 33 of the dataset. In version 30 we added a few additional historical tweets in Russian provided by our coauthors.

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 (776,267,004 unique tweets), and a cleaned version with no retweets on the full_dataset-clean.tsv file (186,617,203 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 (8.4 GB)
Name Size
emojis.zip
md5:81b3d2eab2a3788f790434e82959d944
4.8 MB Download
frequent_bigrams.csv
md5:5ea1ac3b493a815636c62c4e4875df26
18.4 kB Download
frequent_terms.csv
md5:bbee33656457883ef249858668d77a67
12.0 kB Download
frequent_trigrams.csv
md5:cbd1755eb01ebbc18206984b16346ab9
24.6 kB Download
full_dataset-statistics.tsv
md5:ca5f27d48bae90c786bbd0ad4e84c12a
5.5 kB Download
full_dataset.tsv.gz
md5:b4553db041c71cd66b1a6b2a6002b619
6.4 GB Download
full_dataset_clean-statistics.tsv
md5:32781714a2afe56350e820a1a8c178b7
5.3 kB Download
full_dataset_clean.tsv.gz
md5:44b78f1c92f526f547804ced040d62b0
1.7 GB Download
hashtags.zip
md5:60141011ab8680ae51c4bfe8661a7070
100.3 MB Download
mentions.zip
md5:26478ebbc9169f08a24683f7243da3e6
167.2 MB Download
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Views 51,279346
Downloads 58,815260
Data volume 70.4 TB408.5 GB
Unique views 39,321268
Unique downloads 15,889135

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