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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 84 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 (1,226,662,145 unique tweets), and a cleaned version with no retweets on the full_dataset-clean.tsv file (314,645,755 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 (13.8 GB)
Name Size
emojis.zip
md5:085c1b00fdeeb9c4997a3d6b198adc9d
10.1 MB Download
frequent_bigrams.csv
md5:064970dd16e9d534ba4006ff558dc0ff
19.0 kB Download
frequent_terms.csv
md5:c067150a69e2d3ddd57d9983685c192b
11.7 kB Download
frequent_trigrams.csv
md5:36677ab5bc43abd7dd373c1a7dd18bff
25.5 kB Download
full_dataset-statistics.tsv
md5:6d5c5a6a38aa74f47504bcc2b8b732e7
12.2 kB Download
full_dataset.tsv.gz
md5:1e93bb08ddd2841026322c9964821c08
10.4 GB Download
full_dataset_clean-statistics.tsv
md5:bca7c61506f82b7474a2479768e0dded
11.8 kB Download
full_dataset_clean.tsv.gz
md5:78db49f4aa532f3587c9be30cd221ca2
3.0 GB Download
hashtags.zip
md5:6c82a046346725c0e7623f91cd9ba02b
170.4 MB Download
mentions.zip
md5:f436d070215f0866accc7abbfe9e22d4
281.5 MB Download
121,656
159,969
views
downloads
All versions This version
Views 121,656670
Downloads 159,969266
Data volume 230.8 TB473.5 GB
Unique views 94,702532
Unique downloads 29,684122

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