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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; Chowell, Gerardo

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.

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 (255,494,846 unique tweets), and a cleaned version with no retweets on the full_dataset-clean.tsv file (59,105,358 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 statistics-full_dataset.tsv and statistics-full_dataset-clean.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. The 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 (2.3 GB)
Name Size
frequent_bigrams.csv
md5:b40ec08b808c4b5dfff2fe171c2c86ef
20.5 kB Download
frequent_terms.csv
md5:2e9277d961c5978c93777910f5459887
13.3 kB Download
frequent_trigrams.csv
md5:138e67a2ce72e3171f59f2257f248bed
25.5 kB Download
full_dataset-clean-statistics.tsv
md5:faf7b6b4bd18c548de96355a4a4b8401
2.1 kB Download
full_dataset-clean.tsv.gz
md5:081245a848388e86a1411dd94cea8b34
460.6 MB Download
full_dataset-statistics.tsv
md5:1aefc8f12aaca30bc7ae969f6a351652
2.1 kB Download
full_dataset.tsv.gz
md5:f0893857578c18357681bdca51fe3bf7
1.8 GB Download
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