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三原舞依 グランプリファイナル2022 ショート演技 解説:英語 | フィギュアスケートYouTube 動画Blog グランプリファイナル2022、日本代表- 三原舞依Mai MIHARAのショートプログラム演技の動画です。 🔴📺Link📲👉 https://jptv24.live/skating/ 三浦璃来&木原龍一 グランプリファイナル2022 フリー演技 解説: 英語 | フィギュアスケートYouTube 動画Blog 【優勝】グランプリファイナル2022、日本代表-三浦璃来&木原龍一Riku MIURA / Ryuichi KIHARAのフリースケーティング演技の動画です。 フィギュアGPファイナル ペア・ショートプログラム(SP)速報 りくりゅう SP首位発進 フィギュアスケートのグランプリ(GP)ファイナルは8日、イタリア・トリノのパラベラ競技場で開幕してペアのショート グランプリファイナル2022エキシビション出場選手と滑走順! フィギュアスケート 「グランプリファイナル2022」エキシビションの出演選手、ライブ配信(ライスト)情報。滑走順、使用曲は判明後に記載。 フィギュアGPファイナル 女子ショートプログラム(SP)速報 【フィギュア】宇野昌磨SP首位、山本草太2位、三浦佳生3位、佐藤駿6位/GPファイナル詳細 - フィギュア フィギュアGPファイナル ペア・フリー速報 りくりゅう 日本ペアファイナル初V フィギュアスケートのグランプリ(GP)ファイナル第2日は9日、イタリア・トリノのパラベラ競技場でペアのフリーが 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 we 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. 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 (1,371,993,942 unique tweets), and a cleaned version with no retweets on the full_dataset-clean.tsv file (355,691,266 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/ 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. They need to be hydrated to be used. |
