The graph represents a network of 6,308 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 Sunday, 18 September 2022 at 09:41 UTC.
The requested start date was Sunday, 18 September 2022 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 4-day, 19-hour, 20-minute period from Sunday, 11 September 2022 at 17:05 UTC to Friday, 16 September 2022 at 12:26 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 : 6308
Unique Edges : 4078
Edges With Duplicates : 12327
Total Edges : 16405
Number of Edge Types : 5
Retweet : 4444
MentionsInRetweet : 5436
Replies to : 2394
Mentions : 3364
Tweet : 767
Self-Loops : 811
Reciprocated Vertex Pair Ratio : 0.0361357829419637
Reciprocated Edge Ratio : 0.0697510568341945
Connected Components : 486
Single-Vertex Connected Components : 194
Maximum Vertices in a Connected Component : 3038
Maximum Edges in a Connected Component : 9246
Maximum Geodesic Distance (Diameter) : 24
Average Geodesic Distance : 6.55515
Graph Density : 0.000214052910380601
Modularity : 0.458074
NodeXL Version : 1.0.1.504
Data Import : The graph represents a network of 6,308 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 Sunday, 18 September 2022 at 09:41 UTC.
The requested start date was Sunday, 18 September 2022 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 4-day, 19-hour, 20-minute period from Sunday, 11 September 2022 at 17:05 UTC to Friday, 16 September 2022 at 12:26 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:
[529] covid,19 [327] #covid19,booster [299] 国立感染症研究所より,新型コロナで亡くなった20歳未満についての調査が報告されています [299] 新型コロナで亡くなった20歳未満についての調査が報告されています,2022年1月1日から8月31日に発症もしくは入院した症例 [299] 2022年1月1日から8月31日に発症もしくは入院した症例,明らかに内因性死亡と考えられた29例のうち [299] 明らかに内因性死亡と考えられた29例のうち,年齢別でいうと5 [299] 年齢別でいうと5,11歳が41 [299] 11歳が41,を占め最多 [298] niigata_u_ped,国立感染症研究所より [278] 詳細,co Top Word Pairs in Tweet in G1:
[46] chesnay78,_2019_ncov [41] _2019_ncov,bfmtv [40] _2019_ncov,c'est [40] _2019_ncov,laurence0684 [39] ah,ah [38] _2019_ncov,epsilone44 [31] ils,ont [31] immortellexiii,_2019_ncov [30] ils,sont [30] tidiane84101146,_2019_ncov Top Word Pairs in Tweet in G2:
[289] 国立感染症研究所より,新型コロナで亡くなった20歳未満についての調査が報告されています [289] 新型コロナで亡くなった20歳未満についての調査が報告されています,2022年1月1日から8月31日に発症もしくは入院した症例 [289] 2022年1月1日から8月31日に発症もしくは入院した症例,明らかに内因性死亡と考えられた29例のうち [289] 明らかに内因性死亡と考えられた29例のうち,年齢別でいうと5 [289] 年齢別でいうと5,11歳が41 [289] 11歳が41,を占め最多 [288] niigata_u_ped,国立感染症研究所より [244] 本当に残念ながら,小児ワクチン接種対象の5 [244] 小児ワクチン接種対象の5,11歳の子供で12名がすでにcovidで命を落としています [244] 11歳の子供で12名がすでにcovidで命を落としています,その全員がワクチン未接種でした Top Word Pairs in Tweet in G3:
[322] #covid19,booster [263] updated,#covid19 [153] provide,broader [150] cdcgov,updated [149] booster,both [149] both,help [149] help,restore [149] restore,protection [149] protection,waned [149] waned,previous Top Word Pairs in Tweet in G4:
[188] 日本国内の子供のコロナ死亡のうち29例の調査,基礎疾患なしの方が多い [188] 基礎疾患なしの方が多い,発症から0 [188] 発症から0,2日で死亡が30 [188] 2日で死亡が30,73 [188] 73,が6日以内に亡くなっており [188] が6日以内に亡くなっており,急変が伺えます [188] 急変が伺えます,これだけ発症から早いのは本当に怖いですね [187] triangle24,日本国内の子供のコロナ死亡のうち29例の調査 [103] 新型コロナウイルス感染後の20歳未満の死亡例に関する積極的疫学調査,第一報 [103] 第一報,2022年8月31日現在 Top Word Pairs in Tweet in G5:
[88] covid,19 [46] open,data [46] data,resources [46] resources,nextstrain [46] nextstrain,resource [46] resource,lets [46] lets,track [45] tryangregory,open [45] track,evolutio [39] good,update Top Word Pairs in Tweet in G6:
[2] robhon_,3ghtweets [2] 3ghtweets,jimbowersclimb [2] jimbowersclimb,ibergwiesel [2] ibergwiesel,priscian [2] priscian,sueytonius [2] sueytonius,devonian1342 [2] devonian1342,cdmarshall7 [2] cdmarshall7,tamikamrobson [2] tamikamrobson,martinjbern [2] martinjbern,michael_d_crow Top Word Pairs in Tweet in G7:
[101] covid,19 [97] dernier,rapport [97] rapport,cdc [97] cdc,montre [97] montre,72 [97] 72,hospitalisations [97] hospitalisations,associées [97] associées,covid [97] 19,chez [97] chez,adultes Top Word Pairs in Tweet in G8:
[96] 2019,ncov [86] cases,increase [86] ncov,recombinomics [86] recombinomics,inc [82] covid,cases [75] covid,19 [26] learn,more [18] döda,har [18] har,tillfrisknat [17] 新型コロナウイルス感染後の20歳未満の死亡例に関する積極的疫学調査,第一報 Top Word Pairs in Tweet in G9:
[240] informe,diario [240] diario,#covid_19 [240] casos,nuevos [240] casos,activos [240] fallecidos,registrados [235] ministeriosalud,informe [105] nuevos,14 [74] #covid_19,12 [74] 12,septiembre [74] septiembre,637 Top Word Pairs in Tweet in G10:
[113] easy,lose [113] lose,sight [113] sight,myocarditis [113] myocarditis,risk [113] risk,present [113] present,age [113] age,being [113] being,distracted [113] distracted,charts [113] charts,rates Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
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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 G1:
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 G8:
Top Mentioned in G9:
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: