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

<em><strong>Version 46 of the dataset. </strong></em> <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> <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 (927,544,889 unique tweets), and a cleaned version with no retweets on the full_dataset-clean.tsv file (233,095,305 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/ </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. They need to be hydrated to be used.</strong><em><strong>本数据集第46版</strong></em> <strong>鉴于新冠病毒肺炎（COVID-19）全球大流行的相关背景，我们发布本次从推特流（Twitter Stream）中采集的、与新冠疫情相关讨论相关的推文数据集。自首次发布以来，我们新增了来自新合作方的补充数据，使本数据集规模扩充至当前体量。专项数据采集工作自3月11日启动，单日可采集超400万条推文。我们新增了新合作方提供的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。第10版新增了约150万条俄语推文，采集时段为1月1日至5月8日，由卡特娅·阿尔捷莫娃（Katya Artemova，NRU HSE）与叶莲娜·图图巴利娜（Elena Tutubalina，KFU）友情提供。自第12版起，我们在对应压缩包中加入了每日话题标签（hashtag）、提及（mention）及表情符号（emoji）及其出现频率。自第14版起<em>我们</em>已在数据集的清洁版中加入了推文标识符及其对应语言属性。自第20版起，我们为所有推文补充了语言与地域位置信息。</strong> <strong>本次从推特流采集的数据覆盖所有语言，但占比最高的语种为英语、西班牙语与法语。我们将所有推文与转发推文（retweet）发布于full_dataset.tsv文件（含927,544,889条唯一推文），并发布无转发内容的清洁版数据集至full_dataset-clean.tsv文件（含233,095,305条唯一推文）。保留转发内容存在多项实际考量，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frequent_terms.csv中的前1000个高频词、frequent_bigrams.csv中的前1000个二元语法（bigram）以及frequent_trigrams.csv中的前1000个三元语法（trigram）。两类数据集的每日通用统计信息分别收录于full_dataset-statistics.tsv与full_dataset-clean-statistics.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/ </strong> <strong>更多细节可在以下链接查阅（更新频率更高）：https://github.com/thepanacealab/covid19_twitter，同时可参阅我们关于本数据集的预印本论文：https://arxiv.org/abs/2004.03688 </strong> <strong>与此前一致，根据推特的条款与条件，本数据集仅可用于研究目的且仅发布推文标识符（附带采集日期与时间），用户需通过标识符获取完整推文内容（即“水化”处理）后方可使用。</strong>