The graph represents a network of 9,144 Twitter users whose tweets in the requested range contained "SARS-NCOV", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Saturday, 28 November 2020 at 12:28 UTC.
The requested start date was Saturday, 28 November 2020 at 01:01 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 13-day, 23-hour, 51-minute period from Saturday, 14 November 2020 at 01:05 UTC to Saturday, 28 November 2020 at 00:56 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 : 9144
Unique Edges : 6677
Edges With Duplicates : 8233
Total Edges : 14910
Number of Edge Types : 5
Replies to : 1867
Mentions : 4187
Tweet : 521
Retweet : 3406
MentionsInRetweet : 4929
Self-Loops : 543
Reciprocated Vertex Pair Ratio : 0.0035845862790003
Reciprocated Edge Ratio : 0.00714356582994345
Connected Components : 1067
Single-Vertex Connected Components : 242
Maximum Vertices in a Connected Component : 5261
Maximum Edges in a Connected Component : 10756
Maximum Geodesic Distance (Diameter) : 28
Average Geodesic Distance : 6.923938
Graph Density : 0.000120557021042828
Modularity : 0.660571
NodeXL Version : 1.0.1.441
Data Import : The graph represents a network of 9,144 Twitter users whose tweets in the requested range contained "SARS-NCOV", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Saturday, 28 November 2020 at 12:28 UTC.
The requested start date was Saturday, 28 November 2020 at 01:01 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 13-day, 23-hour, 51-minute period from Saturday, 14 November 2020 at 01:05 UTC to Saturday, 28 November 2020 at 00:56 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 : SARS-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:
[1229] sars,cov [866] showing,masks [856] controlled,trial [852] randomized,controlled [851] large,randomized [851] trial,published [851] published,top [851] top,medical [851] medical,journal [851] journal,showing Top Word Pairs in Tweet in G1:
[831] large,randomized [831] randomized,controlled [831] controlled,trial [831] trial,published [831] published,top [831] top,medical [831] medical,journal [831] journal,showing [831] showing,masks [830] jamestodaromd,large Top Word Pairs in Tweet in G2:
[255] infections,spread [255] spread,asymptomatic [254] people,24 [254] 24,transmit [253] drleanawen,important [253] important,info [253] info,cdcgov [253] cdcgov,nearly [253] nearly,60 [253] 60,#covid19 Top Word Pairs in Tweet in G3:
[659] sars,cov [643] ministerio,sanidad [642] sanidad,sanidadgob [641] cov,transmite [641] transmite,aerosoles [641] aerosoles,publica [641] publica,ministerio [641] sanidadgob,hoy [641] hoy,implica [640] mc_minguillon,sars Top Word Pairs in Tweet in G4:
[49] general,positive [49] positive,antibody [49] antibody,test [49] test,presumed [49] presumed,mean [49] mean,person [49] sars,cov [48] person,infected [48] covid,19 [47] infected,sars Top Word Pairs in Tweet in G5:
[113] sars,cov [80] covid,19 [48] scholars,portal [27] 2019,ncov [26] #covid19,#sarscov2 [25] cloth,masks [24] 2020,11 [24] articles,covid [24] portal,périodiques [24] 19,scholars Top Word Pairs in Tweet in G6:
[31] covid,19 [29] sverige,hävdas [29] hävdas,inget [29] inget,stöd [29] stöd,ansiktsmasker [29] ansiktsmasker,erbjuder [29] erbjuder,effektivt [29] effektivt,skydd [29] skydd,mot [29] mot,covid Top Word Pairs in Tweet in G7:
[25] masks,help [25] help,prevent [25] prevent,people [25] people,getting [25] getting,spreading [25] spreading,#covid19 [25] #covid19,masks [25] masks,effective [25] effective,widely [25] widely,used Top Word Pairs in Tweet in G8:
[4] govmikedewine,cdc [4] masks,work [3] sars,cov [3] infections,spread [3] govmikedewine,govwhitmer [3] govwhitmer,govpritzker [3] govpritzker,govholcomb [3] govholcomb,govandybeshear [3] govandybeshear,govtimwalz [3] govtimwalz,govevers Top Word Pairs in Tweet in G9:
[6] governorkayivey,alpublichealth [3] reduce,spread [3] spread,virus [3] masks,help [3] total,192 [3] 192,759 [3] 759,active [3] active,covid [3] covid,19 [3] 19,cases Top Word Pairs in Tweet in G10:
[77] thanks,#opendata [77] #opendata,sharing [77] sharing,gisaid [77] gisaid,we've [77] we've,updated [77] #covid19,#sarscov2 [68] #sarscov2,sequences [66] nextstrain,thanks [19] sars,cov [11] updated,3945 Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Tweeters in Entire Graph:
Top Tweeters in G1:
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Top Tweeters in G9:
Top Tweeters in G10: