The graph represents a network of 3,271 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, 15 August 2022 at 05:28 UTC.
The requested start date was Monday, 15 August 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 9-day, 6-hour, 9-minute period from Friday, 05 August 2022 at 05:09 UTC to Sunday, 14 August 2022 at 11:18 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 : 3271
Unique Edges : 3101
Edges With Duplicates : 14263
Total Edges : 17364
Number of Edge Types : 5
MentionsInRetweet : 6615
Mentions : 4203
Retweet : 5158
Tweet : 995
Replies to : 393
Self-Loops : 1694
Reciprocated Vertex Pair Ratio : 0.0372951591636843
Reciprocated Edge Ratio : 0.0719084801162157
Connected Components : 252
Single-Vertex Connected Components : 167
Maximum Vertices in a Connected Component : 2750
Maximum Edges in a Connected Component : 16648
Maximum Geodesic Distance (Diameter) : 12
Average Geodesic Distance : 4.302471
Graph Density : 0.000514857187198782
Modularity : 0.271479
NodeXL Version : 1.0.1.502
Data Import : The graph represents a network of 3,271 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, 15 August 2022 at 05:28 UTC.
The requested start date was Monday, 15 August 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 9-day, 6-hour, 9-minute period from Friday, 05 August 2022 at 05:09 UTC to Sunday, 14 August 2022 at 11:18 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:
[1808] #ehealth,#finserv [1779] #healthtech,#datascientist [1775] #finserv,#cloud [1762] #cloud,#insurtech [1740] #datascientist,#csuite [1740] #csuite,#digitalhealth [1740] #digitalhealth,#web3 [1739] #web3,#cx [1739] #cx,#ehealth [1133] chidambara09,#healthtech Top Word Pairs in Tweet in G1:
[1591] #ehealth,#finserv [1574] #healthtech,#datascientist [1571] #finserv,#cloud [1562] #cloud,#insurtech [1547] #datascientist,#csuite [1547] #csuite,#digitalhealth [1547] #digitalhealth,#web3 [1546] #web3,#cx [1546] #cx,#ehealth [939] chidambara09,#healthtech Top Word Pairs in Tweet in G2:
[108] #ehealth,#finserv [107] #aimedisnft,#nft [103] #healthcare,#aimx [103] #aimx,#aimxtoken [103] #finserv,#cloud [102] #cloud,#insurtech [101] #medicine,#medtwitter [101] #medtwitter,#healthcare [101] #aimxtoken,#metaverse [101] #metaverse,#token Top Word Pairs in Tweet in G3:
[29] cdcemergency,cdc_ehealth [15] cdcgov,cdcdirector [13] cdc_ehealth,cdc [12] us_fda,cdc_ehealth [11] cdcdirector,cdc_ehealth [10] cdcdirector,cdcemergency [9] cdc_ehealth,cdcflu [9] cdcgov,cdc_ehealth [9] cdc_ehealth,cdcglobal [8] cdcdirector,cdcgov Top Word Pairs in Tweet in G4:
[182] _atanas_,#dhpsp [163] #dhpsp,#crbiotech [113] #crbiotech,#inpst [112] artificial,intelligence [106] #ehealth,#digitalhealth [106] #ehealth,#finserv [104] #healthtech,#datascientist [98] chidambara09,#healthtech [98] #finserv,#cloud [96] #cloud,#insurtech Top Word Pairs in Tweet in G5:
[184] #digitalindia,#avail [184] #avail,#multiple [184] #multiple,#services [184] #services,#janaushadhisugam [184] #janaushadhisugam,#umang [184] #umang,#app [184] #app,#search [184] #search,#medicines [184] #medicines,look [184] look,nearby Top Word Pairs in Tweet in G6:
[75] selected,ceo [73] ehealth,ontario [61] add,ontario [60] ontario,healthcare [60] healthcare,managers [60] nurse,allowed [60] allowed,two [60] two,full [59] full,time [58] managers,one Top Word Pairs in Tweet in G7:
[30] videoident,verfahren [29] chaos,computer [28] computer,club [28] hackt,videoident [27] club,hackt [17] ehealth,inc [16] ehth,ehealth [15] 2022,results [10] q2,2022 [9] announces,second Top Word Pairs in Tweet in G8:
[110] chaos,computer [110] computer,club [110] club,hackt [110] hackt,videoident [110] videoident,verfahren [109] verfahren,die [109] die,identifizierungsmethode [109] identifizierungsmethode,#videoident [109] #videoident,die [109] die,einrichtung Top Word Pairs in Tweet in G9:
[88] social,media [88] media,accounts [88] accounts,dxy [88] dxy,china [88] china,leading [88] leading,ehealth [88] ehealth,platform [88] platform,dedicated [88] dedicated,spreading [88] spreading,public Top Word Pairs in Tweet in G10:
[6] participation,one [6] one,rights [6] rights,principles [6] principles,digital [6] digital,age [6] age,more [6] more,information [6] ztg_nrw,freuen [6] keynote,presentation [6] presentation,annatina Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
Top Replied-To in G3:
Top Replied-To in G4:
Top Replied-To in G6:
Top Replied-To in G8:
Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
Top Mentioned in G2:
Top Mentioned in G3:
Top Mentioned in G4:
Top Mentioned in G5:
Top Mentioned in G6:
Top Mentioned in G7:
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:
Top Tweeters in G6:
Top Tweeters in G7:
Top Tweeters in G8:
Top Tweeters in G9:
Top Tweeters in G10: