A large-scale COVID-19 Twitter chatter dataset for open scientific research - an international collaboration

<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.</strong> <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 (255,494,846 unique tweets), and a cleaned version with no retweets on the full_dataset-clean.tsv file (59,105,358</strong><strong> 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/ </strong> <strong>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) </strong> <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. The need to be hydrated to be used. </strong>鉴于新冠疫情（COVID-19）的全球关联性，我们发布从推特数据流中采集的、与新冠相关讨论的推文数据集。自首次发布以来，我们从新合作方处获取了额外数据，使该资源规模扩充至当前体量。专属数据采集工作始于3月11日，单日可获取超400万条推文。此外我们新增了合作方提供的1月27日至3月27日期间的数据，以拓展数据集的纵向覆盖范围。 本次采集的数据流覆盖所有语言，但使用占比更高的语种包括英语、西班牙语与法语。我们将全部推文及转发（retweet）内容发布于full_dataset.tsv文件（含255,494,846条唯一推文），同时发布不含转发内容的清理版数据集至full_dataset-clean.tsv文件（含59,105,358条唯一推文）。保留转发内容存在多项实际意义，其中之一便是追踪重要推文及其传播路径。 针对自然语言处理（Natural Language Processing, NLP）任务，我们提供了频率最高的1000个单词语项（frequent_terms.csv）、频率最高的1000个二元语法（bigram）文件（frequent_bigrams.csv），以及频率最高的1000个三元语法（trigram）文件（frequent_trigrams.csv）。两个数据集的每日通用统计信息已分别存储于statistics-full_dataset.tsv与statistics-full_dataset-clean.tsv文件中。如需获取更多统计数据与可视化内容，请访问：http://www.panacealab.org/covid19/ 更多细节可在更新速度更快的https://github.com/thepanacealab/covid19_twitter 查询，同时可参阅本数据集的预印本论文：https://arxiv.org/abs/2004.03688 按照推特的服务条款，本页面分发的推文仅包含推文标识符（附带日期与时间信息），仅可用于研究目的。该数据集需经水化处理后方可使用。