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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 78 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 (1,198,902,806 unique tweets), and a cleaned version with no retweets on the full_dataset-clean.tsv file (306,791,449 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 (13.5 GB)
Name Size
emojis.zip
md5:9156c969b4c20170502eda86972b9cf0
9.6 MB Download
frequent_bigrams.csv
md5:0ed54e8e6e07187d0042d56be30a9af7
19.3 kB Download
frequent_terms.csv
md5:f108192167a389847da3c2b002eb1d8b
11.8 kB Download
frequent_trigrams.csv
md5:152043106dc0aa2d1b57c33538ddfecf
26.0 kB Download
full_dataset-statistics.tsv
md5:83f53a80bafebc6b6197d322e8c60934
11.5 kB Download
full_dataset.tsv.gz
md5:d45339a4a33974333ca07e1ff854b982
10.1 GB Download
full_dataset_clean-statistics.tsv
md5:cc58835af033d14b00b090081833926c
11.0 kB Download
full_dataset_clean.tsv.gz
md5:4ffeec1c7729541d362b8eb00ed3f2bb
2.9 GB Download
hashtags.zip
md5:85fa82da7b5b3cf2d38fdf9d89692e41
165.3 MB Download
mentions.zip
md5:cf29e382004f14e23b97d117a616d819
271.9 MB Download
108,630
149,559
views
downloads
All versions This version
Views 108,630738
Downloads 149,559344
Data volume 216.7 TB659.2 GB
Unique views 85,127588
Unique downloads 27,326137

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