The graph represents a network of 1,281 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, 14 November 2022 at 06:27 UTC.
The requested start date was Monday, 14 November 2022 at 01:01 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 3-day, 10-hour, 7-minute period from Monday, 31 October 2022 at 01:11 UTC to Thursday, 03 November 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 : 1281
Unique Edges : 1180
Edges With Duplicates : 4707
Total Edges : 5887
Number of Edge Types : 5
Retweet : 1786
MentionsInRetweet : 2000
Mentions : 1534
Tweet : 447
Replies to : 120
Self-Loops : 854
Reciprocated Vertex Pair Ratio : 0.0461942257217848
Reciprocated Edge Ratio : 0.0883090817862519
Connected Components : 110
Single-Vertex Connected Components : 58
Maximum Vertices in a Connected Component : 963
Maximum Edges in a Connected Component : 5408
Maximum Geodesic Distance (Diameter) : 10
Average Geodesic Distance : 4.134828
Graph Density : 0.00121548106947697
Modularity : 0.29447
NodeXL Version : 1.0.1.507
Data Import : The graph represents a network of 1,281 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, 14 November 2022 at 06:27 UTC.
The requested start date was Monday, 14 November 2022 at 01:01 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 3-day, 10-hour, 7-minute period from Monday, 31 October 2022 at 01:11 UTC to Thursday, 03 November 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:
[925] #datascientist,#csuite [922] #web3,#cx [922] #digitalhealth,#web3 [922] #csuite,#digitalhealth [921] #healthtech,#datascientist [918] #ehealth,#finserv [917] #cx,#ehealth [907] #finserv,#cloud [544] chidambara09,#healthtech [543] #cloud,#insurtechâ Top Word Pairs in Tweet in G1:
[143] î,î [52] vii,#hackathonsalud [40] #web3,#cx [40] #healthtech,#datascientist [40] #digitalhealth,#web3 [40] #csuite,#digitalhealth [40] #datascientist,#csuite [40] #cx,#ehealth [40] #ehealth,#finserv [39] #finserv,#cloud Top Word Pairs in Tweet in G2:
[877] #datascientist,#csuite [874] #web3,#cx [874] #digitalhealth,#web3 [874] #csuite,#digitalhealth [873] #healthtech,#datascientist [870] #ehealth,#finserv [869] #cx,#ehealth [861] #finserv,#cloud [498] chidambara09,#healthtech [497] #cloud,#insurtechâ Top Word Pairs in Tweet in G3:
[10] vaccines,antibiotics [10] #tigray,vaccines [10] antibiotics,insulin [10] patients,tigray [10] insulin,deaths [10] medicine,patients [10] tigray,#tigray [9] soloda12,medicine [9] deaths,prevenâ [9] cdc_ehealth,cdcdirector Top Word Pairs in Tweet in G4:
[17] #iot,#iiot [16] #ar,#vr [11] #iiot,#iotpl [11] future,#medicaleducation [11] #medicaleducation,columbiasurgery [11] columbiasurgery,analytics_699 [11] âš,future [10] eli_krumova,âš [10] #vr,#mr [9] #ehealth,#digitalhealth Top Word Pairs in Tweet in G5:
[36] #marketing,#ar [36] #fintech,#finserv [36] #finserv,#ehealth [26] #metaverse,#marketing [26] #ehealth,enricomolinari [26] vr,#fintech [26] #ar,vr [14] capitalization,#meta [14] market,capitalization [14] #meta,#metaverse Top Word Pairs in Tweet in G6:
[5] review,coverage [5] annual,enrollment [5] options,annual [5] ehealth,survey [5] medicare,beneficiaries [5] survey,highlights [5] coverage,options [5] highlights,medicare [5] beneficiaries,review [4] #keto,#diet Top Word Pairs in Tweet in G7:
[55] siguiente,enlace [55] mã,informaciã [55] aquã,votar [55] votar,ingresar [55] µðÿ,ª [55] final,#brainchile [55] ingresar,siguiente [55] llegã,final [55] informaciã,aquã [36] voto,ganar Top Word Pairs in Tweet in G8:
[12] #domains,#blockchain [12] available,acquisition [12] acquisition,#domains [11] europe,uocuniversity [11] study,europe [11] shows,telemedicine [11] centre,ehealth [11] uocuniversity,collaborating [11] telemedicine,clear [11] ehealth,shows Top Word Pairs in Tweet in G9:
[11] webinar,series [9] inviting,applications [6] #msteams,training [6] #ehealth4all,jcwemyss [6] know,ehealth [6] series,available [6] introduction,training [6] training,video [6] check,introduction [6] âž,#ehealth4all Top Word Pairs in Tweet in G10:
[9] unocha,eucourtpress [9] un_women,unhumanrights [9] unhumanrights,unocha [9] eucourtpress,potos [9] statedept,ehealth_eu [9] potos,statedept [8] ifrc,redcross [8] ehealth_eu,ifrc [8] redcross,redcrosseu [7] britishredcross,redcrosscanada 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 G7:
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:
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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: