The graph represents a network of 8,423 Twitter users whose tweets in the requested range contained "COVID-19", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 05 October 2022 at 07:13 UTC.
The requested start date was Wednesday, 05 October 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 2-day, 0-hour, 21-minute period from Sunday, 02 October 2022 at 11:56 UTC to Tuesday, 04 October 2022 at 12:17 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 : 8423
Unique Edges : 3927
Edges With Duplicates : 12591
Total Edges : 16518
Number of Edge Types : 5
Retweet : 5847
MentionsInRetweet : 6593
Tweet : 2215
Mentions : 1414
Replies to : 449
Self-Loops : 2263
Reciprocated Vertex Pair Ratio : 0.00491273432449903
Reciprocated Edge Ratio : 0.00977743470989322
Connected Components : 2004
Single-Vertex Connected Components : 768
Maximum Vertices in a Connected Component : 2202
Maximum Edges in a Connected Component : 6248
Maximum Geodesic Distance (Diameter) : 30
Average Geodesic Distance : 12.55115
Graph Density : 0.000109573776476206
Modularity : 0.513423
NodeXL Version : 1.0.1.504
Data Import : The graph represents a network of 8,423 Twitter users whose tweets in the requested range contained "COVID-19", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 05 October 2022 at 07:13 UTC.
The requested start date was Wednesday, 05 October 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 2-day, 0-hour, 21-minute period from Sunday, 02 October 2022 at 11:56 UTC to Tuesday, 04 October 2022 at 12:17 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 : COVID-19
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:
[5475] covid,19 [332] non,profit [331] shadowy,nyc [331] nyc,non [331] profit,run [331] run,scientist [331] scientist,tried [331] tried,squelch [331] squelch,theory [331] theory,covid Top Word Pairs in Tweet in G1:
[722] covid,19 [37] 19,pandemic [31] contra,covid [22] 19,vaccine [20] pandemia,covid [19] casos,covid [15] 19,booster [15] 19,travel [14] during,covid [13] 24,horas Top Word Pairs in Tweet in G2:
[665] covid,19 [262] vtvcanal8,#prevención [190] venezuela,registra [171] 19,venezuela [166] contra,covid [149] uso,adecuado [149] adecuado,mascarilla [149] mascarilla,indica [149] indica,métodos [149] métodos,preventivos Top Word Pairs in Tweet in G3:
[343] covid,19 [325] shadowy,nyc [325] nyc,non [325] non,profit [325] profit,run [325] run,scientist [325] scientist,tried [325] tried,squelch [325] squelch,theory [325] theory,covid Top Word Pairs in Tweet in G4:
[103] 30,millions [103] millions,doses [103] doses,vaccins [55] covid19,france [55] france,sûrement [55] sûrement,devoir [55] devoir,détruire [55] détruire,30 [55] vaccins,plus [55] plus,personne Top Word Pairs in Tweet in G5:
[133] covid,19 [41] contre,covid [35] sont,plus [29] médecin,ravise [29] ravise,quant [29] quant,aux [29] aux,#vaccins [29] #vaccins,arnm [29] arnm,covid [29] 19,réclame Top Word Pairs in Tweet in G6:
[84] covid,19 [50] 19,boosters [48] norway,recommend [48] recommend,covid [48] boosters,healthy [48] healthy,individuals [48] individuals,lt [48] lt,65 [48] 65,years [48] years,age Top Word Pairs in Tweet in G7:
[99] covid,19 [65] georgia,cop [65] cop,pushed [65] pushed,people [65] people,take [65] take,horse [65] horse,dewormer [65] dewormer,instead [65] instead,vaccine [65] vaccine,dies Top Word Pairs in Tweet in G8:
[103] covid,19 [78] take,covid [78] 19,jab [77] breaking,swedish [77] swedish,public [77] public,health [77] health,authority [77] authority,stopped [77] stopped,recommending [77] recommending,children Top Word Pairs in Tweet in G9:
[58] covid,19 [43] bolsonaro,recusou [43] recusou,compra [43] compra,vacinas [43] vacinas,brasil [43] brasil,pra [43] pra,primeiros [43] primeiros,países [43] países,serem [43] serem,vacinas Top Word Pairs in Tweet in G10:
[64] covid,19 [34] 19,vaccines [25] sweden,stops [25] stops,recommending [25] recommending,covid [25] vaccines,children [24] zerohedge,sweden [13] 19,vaccine [9] coast,guard [9] guard,rescue Top Replied-To in Entire Graph:
Top Replied-To in G2:
Top Replied-To in G3:
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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:
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Top Mentioned in G7:
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Top Mentioned in G9:
Top Mentioned in G10:
Top Tweeters in Entire Graph:
Top Tweeters in G1:
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Top Tweeters in G5:
Top Tweeters in G6:
Top Tweeters in G7:
Top Tweeters in G8:
Top Tweeters in G9:
Top Tweeters in G10: