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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 77 of the dataset. The peer-reviewed publication for this dataset has now been published  in Epidemiologia an MDPI journal, and can be accessed here: https://doi.org/10.3390/epidemiologia2030024. Please cite this when using 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 (1,192,869,929 unique tweets), and a cleaned version with no retweets on the full_dataset-clean.tsv file (305,057,971 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 (13.4 GB)
Name Size
emojis.zip
md5:6e298b6c1c6dcb98951c14cb00609dd3
9.5 MB Download
frequent_bigrams.csv
md5:c32e99e3dae27344dd9afd726454300c
19.7 kB Download
frequent_terms.csv
md5:27da9544ff4d115892b402713e0e4c96
11.9 kB Download
frequent_trigrams.csv
md5:66934286fac0796573349d4330674d3e
26.9 kB Download
full_dataset-statistics.tsv
md5:382095eea4a21c677d3a2ff7c4adcd90
11.3 kB Download
full_dataset.tsv.gz
md5:e6c918f4a91ec2b59b0a8b48ce71d13a
10.1 GB Download
full_dataset_clean-statistics.tsv
md5:d38f735254197627b7cef82b9771265a
10.9 kB Download
full_dataset_clean.tsv.gz
md5:3256e43e0451876cb2a3985c773c2b60
2.9 GB Download
hashtags.zip
md5:082fa81896223c7df13e3bed487aeba2
164.3 MB Download
mentions.zip
md5:7c2186c1386ac7f9e1ba04ba4f689742
270.1 MB Download
108,630
149,559
views
downloads
All versions This version
Views 108,630571
Downloads 149,559295
Data volume 216.7 TB360.3 GB
Unique views 85,127469
Unique downloads 27,326131

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