The graph represents a network of 2,948 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, 31 January 2022 at 06:27 UTC.
The requested start date was Monday, 31 January 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 8-day, 9-hour, 31-minute period from Friday, 21 January 2022 at 01:47 UTC to Saturday, 29 January 2022 at 11:19 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 : 2948
Unique Edges : 3859
Edges With Duplicates : 15150
Total Edges : 19009
Number of Edge Types : 5
Retweet : 4944
MentionsInRetweet : 7895
Mentions : 4870
Tweet : 1071
Replies to : 229
Self-Loops : 2005
Reciprocated Vertex Pair Ratio : 0.043066178915863
Reciprocated Edge Ratio : 0.0825761198788458
Connected Components : 255
Single-Vertex Connected Components : 146
Maximum Vertices in a Connected Component : 2115
Maximum Edges in a Connected Component : 17527
Maximum Geodesic Distance (Diameter) : 13
Average Geodesic Distance : 3.879411
Graph Density : 0.000722050665327157
Modularity : 0.274887
NodeXL Version : 1.0.1.447
Data Import : The graph represents a network of 2,948 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, 31 January 2022 at 06:27 UTC.
The requested start date was Monday, 31 January 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 8-day, 9-hour, 31-minute period from Friday, 21 January 2022 at 01:47 UTC to Saturday, 29 January 2022 at 11:19 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:
[3139] #women,#ehealth [3136] #cx,#women [2865] #datascientist,#digital [2864] #digital,#cx [2827] #finserv,#fashiontech [2818] #ces2023,#finserv [2761] #fashiontech,#insurtech [2711] #ehealth,#data [2711] #data,#ces2023 [1804] chidambara09,#datascientist Top Word Pairs in Tweet in G1:
[261] #women,#ehealth [260] #cx,#women [241] #datascientist,#digital [241] #digital,#cx [237] #finserv,#fashiontech [228] #ces2023,#finserv [223] #ehealth,#data [223] #data,#ces2023 [222] #ehealth,#digital [221] #fashiontech,#insurtech Top Word Pairs in Tweet in G2:
[2877] #women,#ehealth [2875] #cx,#women [2623] #datascientist,#digital [2622] #digital,#cx [2589] #ces2023,#finserv [2589] #finserv,#fashiontech [2539] #fashiontech,#insurtech [2487] #ehealth,#data [2487] #data,#ces2023 [1594] chidambara09,#datascientist Top Word Pairs in Tweet in G3:
[20] study,highlights [20] highlights,peer [20] peer,led [20] led,group [20] group,intervention [20] intervention,improved [20] improved,ehealth [20] ehealth,literacy [20] literacy,hiv [20] hiv,health Top Word Pairs in Tweet in G4:
[128] qr,code [127] niet,iedereen [127] iedereen,massaal [127] massaal,opstaat [127] opstaat,tegen [127] tegen,qr [127] code,dan [127] dan,zitten [127] zitten,vanaf [127] vanaf,juni Top Word Pairs in Tweet in G5:
[14] digital,health [13] ehealth,ventures [13] 30,million [12] ehealth,inc [10] ventures,raises [10] raises,30 [9] ecosoft,ehealth [9] tm,forum [9] class,action [9] million,digital Top Word Pairs in Tweet in G6:
[10] ehealth,ontario [8] remember,ehealth [8] 8b,tax [8] tax,payer [8] payer,money [8] money,invested [8] invested,lost [8] lost,ontarians [8] ontarians,still [8] still,lack Top Word Pairs in Tweet in G7:
[14] neglected,tropical [14] tropical,diseases [13] diseases,#ntds [12] #chatbots,major [12] major,impact [12] impact,#ehealth [12] #ehealth,domain [12] domain,patient [12] patient,triage [12] triage,patient Top Word Pairs in Tweet in G8:
[8] project,coordinator [6] coordinator,gianna [6] gianna,tsakou [6] tsakou,presented [6] presented,common [6] common,challenges [6] challenges,eu [6] eu,cancer [6] cancer,imaging [6] imaging,infrastructure Top Word Pairs in Tweet in G9:
[15] sachverständigenrats,gesundheit [14] folge,129 [14] 129,online [14] online,prof [14] prof,ferd_gerlach [14] ferd_gerlach,vorsitzender [14] vorsitzender,sachverständigenrats [14] gesundheit,diskutiert [14] diskutiert,cwache [14] cwache,die Top Word Pairs in Tweet in G10:
[19] transformación,digital [19] digital,mejora [15] mejora,salud [13] #savethedate,feb [13] feb,jornada [13] jornada,transformación [13] salud,presencial [13] presencial,virtual [13] virtual,debate [12] fundacionimas,#savethedate 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:
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Top Tweeters in Entire Graph:
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Top Tweeters in G10: