5792072
doi
10.5281/zenodo.5792072
oai:zenodo.org:5792072
user-covid-19
user-biohackathon
Tekumalla, Ramya
Georgia State University
Wang, Guanyu
University of Missouri
Yu, Jingyuan
Universitat Autònoma de Barcelona
Liu, Tuo
Carl von Ossietzky Universität Oldenburg
Ding, Yuning
Universität Duisburg-Essen
Artemova, Katya
NRU HSE
Tutubalina, Elena
KFU
Chowell, Gerardo
Georgia State University
A large-scale COVID-19 Twitter chatter dataset for open scientific research - an international collaboration
Banda, Juan M.
Georgia State University
url:http://www.panacealab.org/covid19/
url:https://arxiv.org/abs/2004.03688
info:eu-repo/semantics/openAccess
Other (Public Domain)
social media
twitter
nlp
covid-19
covid19
<p><em><strong>Version 93 of the dataset. The peer-reviewed publication for this dataset has now been published in Epidemiologia an MDPI journal, and can be accessed here: <a href="https://doi.org/10.3390/epidemiologia2030024">https://doi.org/10.3390/epidemiologia2030024</a>. Please cite this when using the dataset.</strong></em></p>
<p><strong>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 <em>we</em> 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.</strong></p>
<p><strong>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 (1,263,496,943 unique tweets), and a cleaned version with no retweets on the full_dataset-clean.tsv file (325,543,056 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: <a href="http://www.panacealab.org/covid19/">http://www.panacealab.org/covid19/</a> </strong></p>
<p><strong>More details can be found (and will be updated faster at: <a href="https://github.com/thepanacealab/covid19_twitter">https://github.com/thepanacealab/covid19_twitter</a>) and our pre-print about the dataset (<a href="https://arxiv.org/abs/2004.03688">https://arxiv.org/abs/2004.03688</a>) </strong></p>
<p><strong>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.</strong></p>
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.
Zenodo
2021-12-19
info:eu-repo/semantics/other
3723939
user-covid-19
user-biohackathon
93
1681733712.160065
177172937
md5:6b605ec36aa1ae70989ca26aafe4e75e
https://zenodo.org/records/5792072/files/hashtags.zip
293796572
md5:c93d28510f0b151fbf19295bf002a617
https://zenodo.org/records/5792072/files/mentions.zip
12887
md5:c429fda89eab08e0082a08d8d10f2605
https://zenodo.org/records/5792072/files/full_dataset_clean-statistics.tsv
3097313419
md5:2f7e835c5a62484f1fa3831a9d1b0a6f
https://zenodo.org/records/5792072/files/full_dataset_clean.tsv.gz
25267
md5:635557528c806765198e38e9137111d6
https://zenodo.org/records/5792072/files/frequent_trigrams.csv
10747432724
md5:2fceb8206b816ba79974f112b12ef771
https://zenodo.org/records/5792072/files/full_dataset.tsv.gz
13358
md5:fd659057aca30545169f7ad24e9f5114
https://zenodo.org/records/5792072/files/full_dataset-statistics.tsv
11693
md5:0e2dd99feb4034500b9d018b4eba89b1
https://zenodo.org/records/5792072/files/frequent_terms.csv
10882592
md5:b04cc07551f8aecd49bc1fd702893e6a
https://zenodo.org/records/5792072/files/emojis.zip
18150
md5:8bc658acb499b2bb43c21fc800c3f969
https://zenodo.org/records/5792072/files/frequent_bigrams.csv
public
http://www.panacealab.org/covid19/
Is continued by
url
https://arxiv.org/abs/2004.03688
Is supplement to
url
10.5281/zenodo.3723939
isVersionOf
doi
Epidemiologia
2
3
315-324
2021-12-19