The graph represents a network of 7,858 Twitter users whose tweets in the requested range contained "NCoV", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 28 October 2020 at 08:49 UTC.
The requested start date was Wednesday, 28 October 2020 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 7,500.
The tweets in the network were tweeted over the 2-day, 10-hour, 52-minute period from Sunday, 25 October 2020 at 13:08 UTC to Wednesday, 28 October 2020 at 00:00 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 : 7858
Unique Edges : 3201
Edges With Duplicates : 11772
Total Edges : 14973
Number of Edge Types : 5
Replies to : 787
Mentions : 1562
Tweet : 1388
Retweet : 5308
MentionsInRetweet : 5928
Self-Loops : 1428
Reciprocated Vertex Pair Ratio : 0.00257104194857916
Reciprocated Edge Ratio : 0.00512889728708328
Connected Components : 1233
Single-Vertex Connected Components : 526
Maximum Vertices in a Connected Component : 3632
Maximum Edges in a Connected Component : 8616
Maximum Geodesic Distance (Diameter) : 19
Average Geodesic Distance : 6.666253
Graph Density : 0.0001200026446257
Modularity : 0.5068
NodeXL Version : 1.0.1.441
Data Import : The graph represents a network of 7,858 Twitter users whose tweets in the requested range contained "NCoV", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 28 October 2020 at 08:49 UTC.
The requested start date was Wednesday, 28 October 2020 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 7,500.
The tweets in the network were tweeted over the 2-day, 10-hour, 52-minute period from Sunday, 25 October 2020 at 13:08 UTC to Wednesday, 28 October 2020 at 00:00 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 : GraphServerTwitterSearch
Graph Term : NCoV
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:
[967] covid,19 [544] 3月26日の航空機内で発生した集団感染の事例です,どうして今頃このような重要な事例報告がされるのだろうか [544] どうして今頃このような重要な事例報告がされるのだろうか,尾身茂の [544] 尾身茂の,旅行自体が感染を起こすことはない [544] 旅行自体が感染を起こすことはない,発言は7月だったわけですが [543] derive_ip,3月26日の航空機内で発生した集団感染の事例です [543] 発言は7月だったわけですが,３月の時点ですでにこのような重要な事例が国内でも発生していたということ [442] 2019,ncov [349] one,best [302] exposed,#covid19 Top Word Pairs in Tweet in G1:
[281] exposed,#covid19 [275] avoid,being [275] being,exposed [273] one,best [272] #covid19,keep [271] #covid19,help [271] help,#slowthespread [271] #slowthespread,#covid19 [271] keep,key [270] #socialdistancing,one Top Word Pairs in Tweet in G2:
[542] 3月26日の航空機内で発生した集団感染の事例です,どうして今頃このような重要な事例報告がされるのだろうか [542] どうして今頃このような重要な事例報告がされるのだろうか,尾身茂の [542] 尾身茂の,旅行自体が感染を起こすことはない [542] 旅行自体が感染を起こすことはない,発言は7月だったわけですが [541] derive_ip,3月26日の航空機内で発生した集団感染の事例です [541] 発言は7月だったわけですが,３月の時点ですでにこのような重要な事例が国内でも発生していたということ [94] 2020,10 [93] 10,23 [93] 23,国立感染症研究所 [93] 国立感染症研究所,航空機内感染が疑われたcovid Top Word Pairs in Tweet in G3:
[201] covid,19 [186] 2019,ncov [129] covid,cases [128] cases,increase [128] ncov,recombinomics [128] recombinomics,inc [30] learn,more [29] trick,treating [27] 2020,10 [24] halloween,activities Top Word Pairs in Tweet in G4:
[129] covid,19 [127] confinament,nocturn [117] vigor,confinament [114] nocturn,contenir [114] 22,pot [113] entra,vigor [111] contenir,els [109] avui,22 [109] 22,entra [109] els,brots Top Word Pairs in Tweet in G5:
[110] datos,#covid19 [77] sigue,recomendaciones [77] recomendaciones,sanitarias [62] actualización,datos [62] información,coronavirus [60] sanidadgob,actualización [60] coronavirus,ht [58] caso,tener [58] síntomas,leves [58] leves,#covid19 Top Word Pairs in Tweet in G6:
[160] voici,information [160] information,cdc [160] cdc,américain [160] américain,faire [160] faire,mal [160] mal,résumé [160] résumé,tests [160] tests,doivent [160] doivent,être [160] être,centre Top Word Pairs in Tweet in G7:
[69] ways,help [66] one,best [64] help,protect [64] protect,yourself [58] #covid19,make [58] make,sure [57] yourself,others [56] mask,one [56] best,ways [56] others,getting Top Word Pairs in Tweet in G8:
[14] 20,49 [14] 50,69 [12] infection,fatality [11] survival,rates [10] updated,survival [9] cdc,recently [9] recently,updated [9] updated,estimated [9] estimated,infection [9] fatality,rates Top Word Pairs in Tweet in G9:
[112] leo,datos [112] datos,oficiales [112] oficiales,ministerio [112] ministerio,sanidad [112] sanidad,#covid19 [112] #covid19,co [112] co,jiuxgk12h1 [112] jiuxgk12h1,busco [112] busco,disipar [112] disipar,dudas Top Word Pairs in Tweet in G10:
[80] germany,holding [80] holding,tough [80] tough,line [80] line,14 [80] 14,day [80] day,rate [80] rate,map [80] map,nordic [80] nordic,countries [79] mackayim,germany Top Replied-To in Entire Graph:
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Top Mentioned in Entire Graph:
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Top Tweeters in Entire Graph:
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