The graph represents a network of 10,432 Twitter users whose tweets in the requested range contained "healthcare", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Monday, 20 June 2022 at 05:11 UTC.
The requested start date was Monday, 20 June 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, 38-minute period from Wednesday, 15 June 2022 at 10:31 UTC to Friday, 17 June 2022 at 11:09 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 : 10432
Unique Edges : 6275
Edges With Duplicates : 11047
Total Edges : 17322
Number of Edge Types : 5
Retweet : 4850
MentionsInRetweet : 5956
Tweet : 2231
Replies to : 1023
Mentions : 3262
Self-Loops : 2332
Reciprocated Vertex Pair Ratio : 0.0152338340257803
Reciprocated Edge Ratio : 0.0300104931794334
Connected Components : 2478
Single-Vertex Connected Components : 913
Maximum Vertices in a Connected Component : 3424
Maximum Edges in a Connected Component : 7382
Maximum Geodesic Distance (Diameter) : 34
Average Geodesic Distance : 12.041303
Graph Density : 8.75788779669849E-05
Modularity : 0.587315
NodeXL Version : 1.0.1.449
Data Import : The graph represents a network of 10,432 Twitter users whose tweets in the requested range contained "healthcare", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Monday, 20 June 2022 at 05:11 UTC.
The requested start date was Monday, 20 June 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, 38-minute period from Wednesday, 15 June 2022 at 10:31 UTC to Friday, 17 June 2022 at 11:09 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 : healthcare
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:
[304] healthcare,system [254] education,healthcare [231] healthcare,workers [225] healthcare,housing [217] over,explanation [217] explanation,trauma [217] trauma,response [217] response,being [217] being,maliciously [217] maliciously,misunderstood Top Word Pairs in Tweet in G1:
[40] learn,more [33] healthcare,system [28] pharmaceuticals,healthcare [28] healthcare,deals [28] deals,alliances [28] alliances,profile [24] healthcare,professionals [20] healthcare,workers [20] universal,healthcare [20] #ehr,#healthcare Top Word Pairs in Tweet in G2:
[86] private,healthcare [45] literally,couldn [45] couldn,give [45] give,less [45] less,monkeys [45] monkeys,patients [45] patients,sajid [45] sajid,know [45] know,fine [45] fine,well Top Word Pairs in Tweet in G3:
[213] over,explanation [213] explanation,trauma [213] trauma,response [213] response,being [213] being,maliciously [213] maliciously,misunderstood [213] misunderstood,social [213] social,punishment [213] punishment,worse [213] worse,based Top Word Pairs in Tweet in G4:
[183] healthcare,housing [182] defunding,police [182] police,radical [182] radical,defunding [182] defunding,education [182] education,healthcare [182] housing,routine [182] routine,nyc [182] nyc,gives [182] gives,over Top Word Pairs in Tweet in G5:
[37] average,wait [37] wait,time [37] time,ottawa [37] ottawa,hospital [37] hospital,emergency [37] emergency,room [37] room,20 [37] 20,hours [37] hours,sink [37] sink,healthcare Top Word Pairs in Tweet in G6:
[143] healthcare,veterans [143] burn,pits [105] voted,against [104] 14,republicans [104] republicans,voted [104] against,healthcare [104] veterans,suffering [104] suffering,burn [68] pits,dems [68] dems,voted Top Word Pairs in Tweet in G7:
[57] long,ignore [57] ignore,collapsed [57] collapsed,healthcare [57] millions,people [57] people,depend [57] depend,hospitals [54] healthcare,#tigray [54] #tigray,millions [48] hospitals,left [30] pgl_ve,long Top Word Pairs in Tweet in G8:
[131] women,pissed [131] pissed,being [131] being,erased [131] erased,language [131] language,mothers [131] mothers,birthing [131] birthing,parents [131] parents,breastfed [131] breastfed,babies [130] esme_saysno,women Top Word Pairs in Tweet in G9:
[17] #ai,#healthcare [7] #healthcare,#healthtech [7] #cloud,#ai [7] #healthtech,#datascientist [7] #datascientist,#mwc22 [7] #mwc22,#ai [7] #ai,#des2022 [7] #des2022,#digitalhealth [7] #digitalhealth,#cx [7] #cx,#women Top Word Pairs in Tweet in G10:
[79] afternoon,ll [79] ll,delivering [79] delivering,keynote [79] keynote,lecture [79] lecture,sold [79] sold,audience [79] audience,1200 [79] 1200,integrative [79] integrative,medicine [78] draseemmalhotra,afternoon 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 G10: