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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 85 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 (1,230,454,704 unique tweets), and a cleaned version with no retweets on the full_dataset-clean.tsv file (315,760,686 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 (13.9 GB)
Name Size
emojis.zip
md5:5a3f16fe8c3e68b1c7b16ee44d0fa233
10.2 MB Download
frequent_bigrams.csv
md5:b12b30085025b6193c490f14c303aa30
18.3 kB Download
frequent_terms.csv
md5:9c3b21a2192dfbe6319dbd04c5a9d58a
11.7 kB Download
frequent_trigrams.csv
md5:947a0e25f28f3520f720d4d120e4de02
25.6 kB Download
full_dataset-statistics.tsv
md5:c286d91f3f307d350512937d59ddd99b
12.3 kB Download
full_dataset.tsv.gz
md5:53467c505c98ba82a910f5dc5f440ce1
10.4 GB Download
full_dataset_clean-statistics.tsv
md5:ac4ee1457907291fe85ede3699d1601b
11.9 kB Download
full_dataset_clean.tsv.gz
md5:7d086d1182fb51ff067eb5e63cad67c3
3.0 GB Download
hashtags.zip
md5:6653624b53411343e11269998821fb63
171.2 MB Download
mentions.zip
md5:2704d8c987dabb2f4b5dece4b907294e
282.9 MB Download
121,463
159,616
views
downloads
All versions This version
Views 121,4631,264
Downloads 159,616410
Data volume 230.2 TB812.4 GB
Unique views 94,5611,000
Unique downloads 29,633198

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