The graph represents a network of 4,167 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 Tuesday, 11 May 2021 at 05:19 UTC.
The requested start date was Monday, 10 May 2021 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 10-day, 15-hour, 34-minute period from Thursday, 29 April 2021 at 08:05 UTC to Sunday, 09 May 2021 at 23:40 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 : 4167
Unique Edges : 4618
Edges With Duplicates : 15023
Total Edges : 19641
Number of Edge Types : 5
Retweet : 5054
MentionsInRetweet : 9078
Mentions : 3758
Tweet : 1440
Replies to : 311
Self-Loops : 1480
Reciprocated Vertex Pair Ratio : 0.0271035598705502
Reciprocated Edge Ratio : 0.0527766837337534
Connected Components : 338
Single-Vertex Connected Components : 177
Maximum Vertices in a Connected Component : 3373
Maximum Edges in a Connected Component : 18456
Maximum Geodesic Distance (Diameter) : 13
Average Geodesic Distance : 4.297098
Graph Density : 0.000438774307560916
Modularity : 0.325972
NodeXL Version : 1.0.1.445
Data Import : The graph represents a network of 4,167 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 Tuesday, 11 May 2021 at 05:19 UTC.
The requested start date was Monday, 10 May 2021 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 10-day, 15-hour, 34-minute period from Thursday, 29 April 2021 at 08:05 UTC to Sunday, 09 May 2021 at 23:40 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:
[669] mashable,enricomolinari [568] wef,enricomolinari [359] #ehealth,#health [337] #ai,#iot [265] seguimiento,#ehealth [221] #finserv,#insurtech [200] #bigdata,#ehealth [199] enricomolinari,#agritech [192] covid,19 [186] techinsider,enricomolinari Top Word Pairs in Tweet in G1:
[656] mashable,enricomolinari [564] wef,enricomolinari [334] #ehealth,#health [321] #ai,#iot [265] seguimiento,#ehealth [221] #finserv,#insurtech [197] enricomolinari,#agritech [193] #bigdata,#ehealth [186] #insurtech,#proptech [185] techinsider,enricomolinari Top Word Pairs in Tweet in G2:
[34] cdcemergency,cdc_ehealth [18] cdcgov,cdcemergency [18] cdcgov,cdc_ehealth [17] cdc_ehealth,cdcemergency [16] cdcdirector,cdcemergency [15] cdc_ehealth,cdcflu [14] cdcgov,cdcdirector [12] cdcdirector,cdc_ehealth [10] whosearo,whosierraleone [10] whosierraleone,whowpro Top Word Pairs in Tweet in G3:
[25] ehealth,inc [14] ãƒ,ム[13] ehth,ehealth [9] covid,19 [8] first,quarter [8] quarter,2021 [8] stock,news [8] news,alerts [8] alerts,app [7] digital,health Top Word Pairs in Tweet in G4:
[13] #cybersecurity,#ehealth [13] #ai,#iot [10] #machinelearning,explained [10] explained,mitsloan [10] mitsloan,#ai [10] #iot,#cloudcomputing [10] #cloudcomputing,#cybersecurity [9] #ehealth,#healthtech [9] globaliqx,#machinelearning [9] big,picture Top Word Pairs in Tweet in G5:
[12] 3a,availability [12] availability,accessibility [12] accessibility,affordability [8] drsarahgarner,3a [7] covid,19 [7] affordability,tradeoffs [7] tradeoffs,innovation [7] innovation,transparency [7] transparency,cross [7] cross,roads Top Word Pairs in Tweet in G6:
[16] companies,appear [16] leader,rapidly [14] appear,leader [14] rapidly,moving [13] bioasq,task [12] medical,alarm [12] device,#ehealth [12] #ehealth,sector [12] well,being [11] draconabelo,companies Top Word Pairs in Tweet in G7:
[10] ehealth,project [9] #ehealth,stakeholder [9] stakeholder,group [8] know,ehealth [8] project,aims [8] aims,develop [8] develop,basis [8] basis,workable [8] workable,interoperable [8] interoperable,secure Top Word Pairs in Tweet in G8:
[26] ehealth,ontario [21] billion,lost [19] lost,ontarians [19] ontarians,without [18] remember,ehealth [18] ontario,billion [18] without,integrated [18] integrated,electric [18] electric,health [18] health,record Top Word Pairs in Tweet in G9:
[51] infermer,l' [51] l',hospitalclinic [51] hospitalclinic,idea [51] idea,#app [51] #app,permet [51] permet,fer [51] fer,seguiment [51] seguiment,familiars [51] familiars,persones [51] persones,ateses Top Word Pairs in Tweet in G10:
[38] indian,news [38] news,agency [38] agency,talking [38] talking,clinical [38] clinical,murders [38] murders,innocent [38] innocent,patients [38] patients,pfizer [38] pfizer,corp [38] corp,rockefeller Top Replied-To in Entire Graph:
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Top Mentioned in Entire Graph:
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Top Tweeters in Entire Graph:
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Top Tweeters in G10: