The graph represents a network of 1,452 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 Thursday, 29 October 2020 at 11:18 UTC.
The requested start date was Thursday, 29 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 13-day, 23-hour, 46-minute period from Thursday, 15 October 2020 at 00:05 UTC to Wednesday, 28 October 2020 at 23:52 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 : 1452
Unique Edges : 997
Edges With Duplicates : 1424
Total Edges : 2421
Number of Edge Types : 5
Tweet : 194
Retweet : 622
MentionsInRetweet : 932
Mentions : 457
Replies to : 216
Self-Loops : 202
Reciprocated Vertex Pair Ratio : 0.00805369127516779
Reciprocated Edge Ratio : 0.0159786950732357
Connected Components : 269
Single-Vertex Connected Components : 81
Maximum Vertices in a Connected Component : 321
Maximum Edges in a Connected Component : 577
Maximum Geodesic Distance (Diameter) : 19
Average Geodesic Distance : 6.611373
Graph Density : 0.000712911965339758
Modularity : 0.627736
NodeXL Version : 1.0.1.441
Data Import : The graph represents a network of 1,452 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 Thursday, 29 October 2020 at 11:18 UTC.
The requested start date was Thursday, 29 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 13-day, 23-hour, 46-minute period from Thursday, 15 October 2020 at 00:05 UTC to Wednesday, 28 October 2020 at 23:52 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:
[445] sars,cov [141] 2019,ncov [140] covid,19 [104] epidemiology,sars [104] cov,indicates [103] indicates,infections [98] #covid19,#sarscov2 [79] ncov,19 [73] chadox1,ncov [70] thanks,#opendata Top Word Pairs in Tweet in G1:
[75] covid,19 [71] sars,cov [52] scholars,portal [26] 2020,10 [26] articles,covid [26] portal,périodiques [26] 19,scholars [26] #covid19,#sarscov2 [26] portal,journals [22] 2019,ncov Top Word Pairs in Tweet in G2:
[70] thanks,#opendata [70] #opendata,sharing [70] sharing,gisaid [70] #covid19,#sarscov2 [62] nextstrain,thanks [49] gisaid,we've [49] we've,updated [49] #sarscov2,sequences [21] #sarscov2,seqs [21] seqs,seqs Top Word Pairs in Tweet in G3:
[64] vacuna,oxford [64] oxford,revela [64] revela,infección [64] infección,chadox1 [64] chadox1,ncov [64] ncov,19 [64] 19,líneas [64] líneas,celulares [64] celulares,humanas [64] humanas,revela Top Word Pairs in Tweet in G4:
[49] salutcat,18 [48] oriolmitja,salutcat [48] 18,dies [48] dies,després [48] després,anterior [48] anterior,ja [48] ja,ho [48] ho,tenim [48] tenim,nou [48] nou,document Top Word Pairs in Tweet in G5:
[54] sars,cov [53] cdc,aclaran [53] aclaran,conceptos [53] conceptos,airborne [53] airborne,droplets [53] droplets,aerosol [53] aerosol,epidemiology [53] epidemiology,sars [53] cov,indicates [53] indicates,infections Top Word Pairs in Tweet in G6:
[10] sars,cov [5] 2019,ncov [4] patricksavalle,yettithaoj [4] yettithaoj,thomas_binder [4] thomas_binder,lynnfynn3 [4] lynnfynn3,c_drosten [4] quantified,virus [4] virus,isolates [4] isolates,2019 [4] ncov,currently Top Word Pairs in Tweet in G7:
[10] sars,cov [6] covid,19 [6] sars,2019 [6] 2019,ncov [5] cov,virus [4] samples,sars [4] gatormomm,reuters [4] reuters,know [4] know,cats [4] cats,dogs Top Word Pairs in Tweet in G8:
[14] sars,cov [11] scientific,brief [11] brief,cdcgov [11] cdcgov,well [11] well,documented [11] documented,examples [11] examples,sars [11] cov,being [11] being,transmitted [11] transmitted,over Top Word Pairs in Tweet in G9:
[70] detección,precoz [35] objetivos,estrategia [35] estrategia,detección [35] precoz,vigilancia [35] vigilancia,control [35] control,#covid19 [35] #covid19,detección [35] precoz,casos [34] sanidadgob,objetivos [34] casos,infec Top Word Pairs in Tweet in G10:
[10] navedelmisterio,silvitrianera [8] lord_juli,almu_rmarin [6] almu_rmarin,francis61470479 [6] francis61470479,observatorio14 [6] observatorio14,lolaneuromd [6] lolaneuromd,navedelmisterio [5] sars,cov [5] silvitrianera,ter [4] epidemiology,sars [4] cov,indicates Top Replied-To in Entire Graph:
Top Replied-To in G4:
Top Replied-To in G6:
Top Replied-To in G7:
Top Replied-To in G8:
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: