The graph represents a network of 16,922 Twitter users whose recent tweets contained "COVID", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 18,000 tweets. The network was obtained from Twitter on Monday, 24 February 2020 at 05:52 UTC.
The tweets in the network were tweeted over the 1-hour, 7-minute period from Monday, 24 February 2020 at 03:33 UTC to Monday, 24 February 2020 at 04:40 UTC.
Additional tweets that were mentioned in this data set were also collected from prior time periods. These tweets may expand the complete time period of the data.
There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, and a self-loop edge for each tweet that is not a "replies-to" or "mentions".
The graph is directed.
The graph's vertices were grouped by cluster using the Clauset-Newman-Moore cluster algorithm.
The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.
Author Description
Vertices : 16922
Unique Edges : 18848
Edges With Duplicates : 2065
Total Edges : 20913
Number of Edge Types : 5
Retweet : 15167
Tweet : 2542
MentionsInRetweet : 1541
Mentions : 871
Replies to : 792
Self-Loops : 2570
Reciprocated Vertex Pair Ratio : 0.000969766115231033
Reciprocated Edge Ratio : 0.00193765316008435
Connected Components : 1796
Single-Vertex Connected Components : 907
Maximum Vertices in a Connected Component : 12846
Maximum Edges in a Connected Component : 16610
Maximum Geodesic Distance (Diameter) : 20
Average Geodesic Distance : 6.758059
Graph Density : 6.12809035244961E-05
Modularity : 0.815018
NodeXL Version : 1.0.1.423
Data Import : The graph represents a network of 16,922 Twitter users whose recent tweets contained "COVID", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 18,000 tweets. The network was obtained from Twitter on Monday, 24 February 2020 at 05:52 UTC.
The tweets in the network were tweeted over the 1-hour, 7-minute period from Monday, 24 February 2020 at 03:33 UTC to Monday, 24 February 2020 at 04:40 UTC.
Additional tweets that were mentioned in this data set were also collected from prior time periods. These tweets may expand the complete time period of the data.
There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, and a self-loop edge for each tweet that is not a "replies-to" or "mentions".
Layout Algorithm : The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.
Graph Source : TwitterSearch
Graph Term : COVID
Groups : The graph's vertices were grouped by cluster using the Clauset-Newman-Moore cluster algorithm.
Edge Color : Edge Weight
Edge Width : Edge Weight
Edge Alpha : Edge Weight
Vertex Radius : Betweenness Centrality
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[8703] covid,19 [3245] ต,ดเช [2595] 先日,コロナ対策で赤字被って死にそうだってツイートしたんですが [2595] コロナ対策で赤字被って死にそうだってツイートしたんですが,経済産業省から事業社へ支援策が出てたので共有 [2595] 経済産業省から事業社へ支援策が出てたので共有,イベント主催 [2595] イベント主催,運営 [2595] 運営,技術周り [2595] 技術周り,スタッフ派遣 [2595] スタッフ派遣,タレント事務所 [2595] タレント事務所,どこまで適用になるか分かりませんが Top Word Pairs in Tweet in G1:
[2557] 先日,コロナ対策で赤字被って死にそうだってツイートしたんですが [2557] コロナ対策で赤字被って死にそうだってツイートしたんですが,経済産業省から事業社へ支援策が出てたので共有 [2557] 経済産業省から事業社へ支援策が出てたので共有,イベント主催 [2557] イベント主催,運営 [2557] 運営,技術周り [2557] 技術周り,スタッフ派遣 [2557] スタッフ派遣,タレント事務所 [2557] タレント事務所,どこまで適用になるか分かりませんが [2557] どこまで適用になるか分かりませんが,良かったら参考にしてください [2557] 良かったら参考にしてください,同業社に届け Top Word Pairs in Tweet in G2:
[2271] ต,ดเช [1303] covid,19 [1243] อ,covid [1183] ดเช,อ [1081] ด,วน [1053] เกาหล,ใต [1038] ยช,ว [992] เส,ยช [959] วน,เกาหล [954] วเลขผ,ต Top Word Pairs in Tweet in G3:
[422] วย,#covid_19 [410] #โคว,ด19 [382] ต,ดเช [351] นธ,ใหม [322] ดเช,อ [309] ด19,#covid_19 [298] #ไวร,สโคโรนา [281] ใหม,2019 [276] ป,วย [261] #covid_19,#ไวร Top Word Pairs in Tweet in G4:
[515] covid,19 [29] coronavirus,covid [29] south,korea [23] 19,outbreak [20] ダイヤモンド,プリンセス号に乗った公衆衛生の専門家 [20] プリンセス号に乗った公衆衛生の専門家,下船後に発症者が出るのは想定されたこと [17] 19,cases [14] 新型コロナウイルス,covid [13] #covid_19,#covid19 [12] cases,covid Top Word Pairs in Tweet in G5:
[829] covid,19 [344] minister,health [343] dr,dzulkefly [343] dzulkefly,one [343] one,best [343] best,minister [343] health,listens [343] listens,everyone [343] everyone,makes [343] makes,right Top Word Pairs in Tweet in G6:
[218] #covid_19,#covid19italia [217] more,business [217] business,#covid_19 [182] stunned,europe [182] europe,biggest [182] biggest,surge [182] surge,#coronavirus [182] #coronavirus,italy [182] italy,appears [182] appears,operating Top Word Pairs in Tweet in G7:
[638] ดเช,อ [571] องก,น [569] อ,#covid_19 [569] #tnnข,าวเท [569] าวเท,ยง [562] ย,งไม [561] กระทรวงสาธารณส,ข [561] ข,เตร [561] เตร,ยมประกาศโรคต [561] ยมประกาศโรคต,ดเช Top Word Pairs in Tweet in G8:
[722] covid,19 [672] ประเทศไทยโชคด,เหม [672] เหม,อนก [672] อนก,นเร [672] นเร,อง [672] อง,covid [672] 19,สาธารฐส [672] สาธารฐส,ขเก [672] ขเก,ง [672] ง,ขนส Top Word Pairs in Tweet in G9:
[507] covid,19 [463] 19,อาจจะทำให [463] อาจจะทำให,หลายประเทศทดสอบการ [463] หลายประเทศทดสอบการ,work [463] work,home [463] home,คร [463] คร,งใหญ [463] งใหญ,ท [463] ท,ส [463] ส,ดเท Top Word Pairs in Tweet in G10:
[282] 今急ぐべきは,covidのpcr検査の緊急保険適応 [282] covidのpcr検査の緊急保険適応,医療機関にはアビガンよりも大量のマスク [282] 医療機関にはアビガンよりも大量のマスク,下船者全員に厚労省から電話でなく地元保健所からのフォロー [282] 下船者全員に厚労省から電話でなく地元保健所からのフォロー,全国の医療機関に感染 [282] 全国の医療機関に感染,疑い [282] 疑い,者対応できる外来スペースと病床の確保の準備 [282] 者対応できる外来スペースと病床の確保の準備,そのための緊急財政支援 [282] そのための緊急財政支援,100億予備費ではダメ [282] 100億予備費ではダメ,ケタ違いの補正予算を [86] covid,19 Top Replied-To in Entire Graph:
Top Replied-To in G2:
Top Replied-To in G3:
Top Replied-To in G4:
Top Replied-To in G5:
Top Replied-To in G6:
Top Replied-To in G7:
Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G2:
Top Mentioned in G3:
Top Mentioned in G4:
Top Mentioned in G5:
Top Mentioned in G6:
Top Mentioned in G7:
Top Mentioned in G10:
Top Tweeters in Entire Graph:
Top Tweeters in G1:
Top Tweeters in G2:
Top Tweeters in G3:
Top Tweeters in G4:
Top Tweeters in G5:
Top Tweeters in G6:
Top Tweeters in G7:
Top Tweeters in G8:
Top Tweeters in G9:
Top Tweeters in G10: