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

<em><strong>Version 62 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 (1,081,454,346 unique tweets), and a cleaned version with no retweets on the full_dataset-clean.tsv file (274,334,787 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>**数据集版本62。** 鉴于新冠病毒肺炎（COVID-19）全球大流行的相关性，我们发布从推特流（Twitter Stream）中获取的与新冠相关讨论的推特数据集。自首次发布以来，我们从新的合作方处获得了额外数据，使本数据集资源规模扩展至当前体量。专项数据采集工作始于3月11日，单日采集量超400万条推特。此外，我们新增了1月27日至3月27日期间的合作方提供数据，以拓展数据集的纵向覆盖范围。 版本10新增了约150万条俄语推特，采集时间为1月1日至5月8日，由Katya Artemova（国家研究型高等经济大学，NRU HSE）与Elena Tutubalina（喀山联邦大学，KFU）慷慨提供。 自版本12起，我们在对应压缩包中新增了每日话题标签、提及内容、表情符号及其出现频率。自版本14起，数据集清洁版包含推特标识符及其对应语言信息。自版本20起，我们新增了所有推特的语言与地点位置信息。 本流数据采集覆盖所有语言，但主流语种为英语、西班牙语与法语。我们发布了完整数据集文件full_dataset.tsv（包含1,081,454,346条唯一推特，涵盖所有推文与转推），以及不含转推的清洁版数据集文件full_dataset-clean.tsv（包含274,334,787条唯一推特）。保留转推存在多项实际考量，其中之一便是便于追踪重要推文及其传播路径。 针对自然语言处理（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个高频二元组，以及frequent_trigrams.csv中的前1000个高频三元组。两个数据集的每日通用统计信息分别存储于full_dataset-statistics.tsv与full_dataset-clean-statistics.tsv文件中。更多统计数据与可视化内容可访问：http://www.panacealab.org/covid19/ 更多细节可在更新更为及时的地址https://github.com/thepanacealab/covid19_twitter 查阅，同时可参阅本数据集的预印本论文https://arxiv.org/abs/2004.03688。 根据推特的服务条款，仅可出于研究目的重新分发推特数据，因此本次发布的内容仅为附带日期与时间信息的推特标识符，需经水化处理后方可正常使用。