The graph represents a network of 4,446 Twitter users whose tweets in the requested range contained "ehealth", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Monday, 30 March 2020 at 06:25 UTC.
The requested start date was Monday, 30 March 2020 at 00:01 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 5-day, 19-hour, 55-minute period from Monday, 23 March 2020 at 18:17 UTC to Sunday, 29 March 2020 at 14:12 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 : 4446
Unique Edges : 7445
Edges With Duplicates : 4438
Total Edges : 11883
Number of Edge Types : 4
MentionsInRetweet : 5829
Replies to : 439
Mentions : 4582
Tweet : 1033
Self-Loops : 1033
Reciprocated Vertex Pair Ratio : 0.0237173885906878
Reciprocated Edge Ratio : 0.0463358127057676
Connected Components : 262
Single-Vertex Connected Components : 120
Maximum Vertices in a Connected Component : 3658
Maximum Edges in a Connected Component : 10978
Maximum Geodesic Distance (Diameter) : 14
Average Geodesic Distance : 4.530207
Graph Density : 0.000414978492060962
Modularity : 0.583013
NodeXL Version : 1.0.1.428
Data Import : The graph represents a network of 4,446 Twitter users whose tweets in the requested range contained "ehealth", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Monday, 30 March 2020 at 06:25 UTC.
The requested start date was Monday, 30 March 2020 at 00:01 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 5-day, 19-hour, 55-minute period from Monday, 23 March 2020 at 18:17 UTC to Sunday, 29 March 2020 at 14:12 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 : ehealth
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:
[383] covid,19 [176] cdcemergency,cdc_ehealth [160] ty,wef [159] seguimiento,#ehealth [145] #healthtech,#ehealth [127] enricomolinari,#healthtech [127] cdcgov,cdcemergency [121] #health,#healthcareit [117] #healthcareit,#ehealth [112] digitale,zorg Top Word Pairs in Tweet in G1:
[161] cdcemergency,cdc_ehealth [116] cdcgov,cdcemergency [68] cdcgov,cdc_ehealth [45] cdcemergency,cdcdirector [45] cdcdirector,cdc_ehealth [40] cdc_ehealth,cdcemergency [34] cdc_ehealth,cdcflu [33] cdc_ehealth,cdcgov [31] congress,senate [28] covid,19 Top Word Pairs in Tweet in G2:
[167] covid,19 [154] seguimiento,#ehealth [121] #health,#healthcareit [117] #healthcareit,#ehealth [111] #doctors,#hospital [110] #hospital,#health [103] #ehealth,#healthcare [83] #healthcare,#digitalhealth [75] #ehealth,#health [68] saludigital_es,#ehealth Top Word Pairs in Tweet in G3:
[155] ty,wef [128] #healthtech,#ehealth [117] enricomolinari,#healthtech [96] wef,enricomolinari [80] aim,#selfdriving [80] #selfdriving,hospital [80] hospital,envisioning [80] envisioning,demand [80] demand,version [80] version,doctor Top Word Pairs in Tweet in G4:
[61] #ehealth,#esalud [56] #covidー19,#covid19 [56] #covid19,#ehealth [55] #esalud,#coronavirus [54] covid,19 [45] #coronavirus,#quedateencasa [41] eres,profesional [41] profesional,hospitalario [41] hospitalario,scsalud [41] scsalud,sabías Top Word Pairs in Tweet in G5:
[75] digitale,zorg [41] zorg,afstand [35] afstand,mogelijk [24] mensen,met [23] minvws,maakt [23] mogelijk,maken [22] digitale,toepassingen [22] niks,aan [21] egerrit,heb [21] heb,niks Top Word Pairs in Tweet in G6:
[12] potus,potus44 [12] potus44,billclinton [11] fcc,ajitpaifcc [9] cdcemergency,cdc_ehealth [8] cdcdirector,cdcemergency [7] nprpolitics,nbcpolitics [7] nbcpolitics,meetthepress [7] cdcflu,cdc_ehealth [7] cdc_ehealth,cdcemergency [7] computer,records Top Word Pairs in Tweet in G7:
[10] tijdens,corona [10] corona,crisis [8] ehealth,ehth [8] digitale,zorg [8] ehealth,inc [7] zorg,afstand [7] covid,19 [6] ehealth,africa [6] inc,ehth [5] mensen,thuis Top Word Pairs in Tweet in G8:
[8] die,#coronapandemie [8] coronavirus,virtuelles [8] virtuelles,krankenhaus [8] krankenhaus,nrw [8] nrw,startet [8] startet,vorzeitig [8] vorzeitig,intensivmedizin [8] intensivmedizin,düsseldorf [8] düsseldorf,hintergrund [7] covid,19 Top Word Pairs in Tweet in G9:
[36] حم,ل [36] الصحة,العامة [24] هل,تشعر [24] تشعر,بأعراض [24] بأعراض,قد [24] قد,تكون [24] تكون,#كورونا [24] #كورونا,وتريد [24] وتريد,تقييم [24] تقييم,سريع Top Word Pairs in Tweet in G10:
[6] diagnose,#covid [6] #covid,19 [6] 19,zentraler [6] zentraler,bedeutung [6] bedeutung,die [6] die,zahl [6] zahl,kontaktpersonen [6] kontaktpersonen,möglichst [6] möglichst,gering [6] gering,halten 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:
Top Mentioned in G2:
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Top Mentioned in G4:
Top Mentioned in G5:
Top Mentioned in G6:
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:
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Top Tweeters in G9:
Top Tweeters in G10: