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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 95 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 (1,280,803,012 unique tweets), and a cleaned version with no retweets on the full_dataset-clean.tsv file (328,851,757 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 (14.5 GB)
Name Size
emojis.zip
md5:36874da86b5bb36f7201b403b15572c9
11.1 MB Download
frequent_bigrams.csv
md5:3d180cae8dab2f8e83a4256caf475a80
18.0 kB Download
frequent_terms.csv
md5:a5dae3b6ecb0f9a93864f6a7ce4a3adc
11.6 kB Download
frequent_trigrams.csv
md5:bf35dba3ba72ed525f4528292fc3efee
24.8 kB Download
full_dataset-statistics.tsv
md5:5de2ed09b51c34c1dc3638b695a04b92
13.6 kB Download
full_dataset.tsv.gz
md5:8e3fadc27b796f7f018c246f2f8b61bb
10.9 GB Download
full_dataset_clean-statistics.tsv
md5:605577325094ad2e08acf093cde50e7c
13.1 kB Download
full_dataset_clean.tsv.gz
md5:7bc354016524a95cbe53ac903f8fef14
3.1 GB Download
hashtags.zip
md5:bd10fdb232c2091bbde88d767a0a7068
178.8 MB Download
mentions.zip
md5:9cc83856d7ab18123c9cc456c748a198
297.0 MB Download
127,357
163,850
views
downloads
All versions This version
Views 127,357430
Downloads 163,850113
Data volume 237.7 TB162.8 GB
Unique views 99,184377
Unique downloads 30,73654

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