The graph represents a network of 1,394 Twitter users whose tweets in the requested range contained "#hcldr", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Thursday, 21 November 2019 at 01:54 UTC.
The requested start date was Tuesday, 19 November 2019 at 01:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 13-day, 23-hour, 40-minute period from Tuesday, 05 November 2019 at 01:20 UTC to Tuesday, 19 November 2019 at 01:00 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 : 1394
Unique Edges : 2914
Edges With Duplicates : 4060
Total Edges : 6974
Number of Edge Types : 3
Mentions : 5389
Replies to : 788
Tweet : 797
Self-Loops : 797
Reciprocated Vertex Pair Ratio : 0.117629086465017
Reciprocated Edge Ratio : 0.210497539639147
Connected Components : 62
Single-Vertex Connected Components : 34
Maximum Vertices in a Connected Component : 1246
Maximum Edges in a Connected Component : 6756
Maximum Geodesic Distance (Diameter) : 11
Average Geodesic Distance : 3.906241
Graph Density : 0.0018837783918568
Modularity : 0.340895
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 1,394 Twitter users whose tweets in the requested range contained "#hcldr", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Thursday, 21 November 2019 at 01:54 UTC.
The requested start date was Tuesday, 19 November 2019 at 01:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 13-day, 23-hour, 40-minute period from Tuesday, 05 November 2019 at 01:20 UTC to Tuesday, 19 November 2019 at 01:00 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 : #hcldr
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 : Followers
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[128] access,health [115] #hcldr,chat [110] #hcldr,#thinkdigitalhealth [106] hcldr,joebabaian [92] #hcldr,#pinksocks [84] #hcldr,#xmed [77] digital,health [73] patients,need [72] #hcldr,#hitsm [69] health,information Top Word Pairs in Tweet in G1:
[67] #hcldr,#xmed [62] #hcldr,#pinksocks [56] hcldr,joebabaian [54] #hcldr,#hitsm [52] #digitalhealth,#hcldr [51] icymi,gt [35] shocked,saddened [35] saddened,news [35] news,bernardjtyson's [35] bernardjtyson's,passing Top Word Pairs in Tweet in G2:
[113] access,health [102] #hcldr,#thinkdigitalhealth [91] #hcldr,chat [60] digital,health [58] patients,need [56] health,information [54] health,week [48] need,access [45] health,records [45] week,canada Top Word Pairs in Tweet in G3:
[14] #pophealth,minute [13] powerful,panel [13] panel,sponsored [13] sponsored,navvispophealth [13] navvispophealth,live [13] live,flaacos [13] flaacos,annual [13] annual,conference [13] conference,impressive [13] impressive,panel Top Word Pairs in Tweet in G4:
[12] better,care [8] donberwick,md [8] md,mpp [8] mpp,frcp [8] frcp,weighs [8] weighs,20 [8] 20,years [8] years,#toerrishuman [8] #toerrishuman,week [8] week,s Top Word Pairs in Tweet in G5:
[20] social,media [8] media,help [8] help,transform [8] transform,humanize [8] humanize,#healthcare [8] #healthcare,social [8] media,guru [8] guru,around [8] around,#digitalhealth [8] #digitalhealth,expert Top Word Pairs in Tweet in G6:
[10] #hcldr,#hitsm [7] health,care [6] #hitsm,#hitmc [6] care,leadership [6] leadership,conference [5] cleaning,up [5] up,bit [5] bit,today [5] today,forgot [5] forgot,scattergoodfdn Top Word Pairs in Tweet in G7:
[10] health,care [8] jlschilling22,new [7] #hitsm,#hcldr [7] learn,more [6] research,suggests [6] more,#hcldr [6] ehr,usability [6] usability,clear [6] clear,return [6] return,investment Top Word Pairs in Tweet in G8:
[5] #hcldr,s4pm [4] patients,suffered [4] suffered,w [4] w,#datablocking [4] #datablocking,long [4] long,enough [4] enough,#unblockhealth [4] #unblockhealth,armed [4] armed,ready [4] ready,end Top Word Pairs in Tweet in G9:
[37] #health,#healthcare [33] artificial,intelligence [33] intelligence,important [33] important,healthcare [33] healthcare,#himss [33] #himss,#healthcare [33] #healthcare,#ai [33] #ai,#airesearch [27] #hcldr,#cio [26] #cio,#samsung Top Word Pairs in Tweet in G10:
[11] hcldr,joebabaian [11] latest,#patientadvocacy [11] #patientadvocacy,blog [11] journey,managing [11] managing,chronic [10] chronic,disease [6] professormac,hcldr [6] want,learn [6] learn,ways [6] ways,engage Top Replied-To in Entire Graph:
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Top Replied-To in G8:
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Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Mentioned in G10:
Top Tweeters in Entire Graph:
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Top Tweeters in G10: