The graph represents a network of 5,340 Twitter users whose tweets in the requested range contained "digitalhealth", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 20 November 2020 at 23:54 UTC.
The requested start date was Friday, 20 November 2020 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 4-day, 19-hour, 11-minute period from Sunday, 15 November 2020 at 05:49 UTC to Friday, 20 November 2020 at 01:00 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 : 5340
Unique Edges : 5868
Edges With Duplicates : 11043
Total Edges : 16911
Number of Edge Types : 5
Mentions : 3693
Retweet : 4075
MentionsInRetweet : 6887
Tweet : 2106
Replies to : 150
Self-Loops : 2231
Reciprocated Vertex Pair Ratio : 0.0587875824981667
Reciprocated Edge Ratio : 0.111046981415214
Connected Components : 839
Single-Vertex Connected Components : 425
Maximum Vertices in a Connected Component : 3437
Maximum Edges in a Connected Component : 13955
Maximum Geodesic Distance (Diameter) : 15
Average Geodesic Distance : 5.18634
Graph Density : 0.000303855524291957
Modularity : 0.448621
NodeXL Version : 1.0.1.441
Data Import : The graph represents a network of 5,340 Twitter users whose tweets in the requested range contained "digitalhealth", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 20 November 2020 at 23:54 UTC.
The requested start date was Friday, 20 November 2020 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 4-day, 19-hour, 11-minute period from Sunday, 15 November 2020 at 05:49 UTC to Friday, 20 November 2020 at 01:00 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 : digitalhealth
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:
[562] digital,health [292] read,more [272] gt,gt [244] #digitalhealth,#healthcare [197] covid,19 [196] #healthcare,#digitalhealth [194] more,#cure [185] #digitalhealth,#healthtech [176] #cure,#digitalhealth [164] #healthcare,#infographic Top Word Pairs in Tweet in G1:
[248] gt,gt [227] read,more [190] #digitalhealth,#healthcare [188] more,#cure [173] #cure,#digitalhealth [164] #healthcare,#infographic [159] #infographic,#iot [152] #iot,#medicaltechnology [152] #medicaltechnology,#medicine [152] #medicine,#medtech Top Word Pairs in Tweet in G2:
[56] digital,health [46] #healthcare,#digitalhealth [21] #lyfebulb,#healthcare [20] covid,19 [19] #digitalhealth,#insights [18] #digitalhealth,#healthcare [18] #digitalhealth,#healthtech [17] #digitalhealth,#hcldr [16] healthcare,#digitalhealth [16] icymi,gt Top Word Pairs in Tweet in G3:
[71] digital,health [58] agents,change [51] #giant2020,speaking [45] forum,agents [44] gianthealthevnt,introducing [42] #digitalhealth,forum [39] conference,track [35] #digitalhealth,#healthtech [31] virtual,#digitalhealth [27] gianthealthevnt,meet Top Word Pairs in Tweet in G4:
[126] thefuturisthq,irmaraste [126] evirahealth,#di [125] remote,procedure [125] procedure,london [125] london,based [125] based,surgeon [125] surgeon,californian [125] californian,banana [125] banana,thefuturisthq [125] irmaraste,zgjr Top Word Pairs in Tweet in G5:
[31] digital,health [23] #digitalhealth,#nhs [19] day,#dhssummit20 [18] #healthtech,#digitalhealth [17] read,more [16] bleddyn_rees,#digitalhealth [15] 24,november [15] #i2m,initiative [14] online,#training [13] openehr,digital Top Word Pairs in Tweet in G6:
[56] digital,health [41] health,week [32] learn,more [22] health,care [13] improve,health [13] health,canadians [12] looking,forward [11] more,pan [11] pan,canadian [11] canadian,health Top Word Pairs in Tweet in G7:
[14] amazon,pharmacy [14] selling,prescription [14] prescription,drugs [13] disruption,amazon [13] pharmacy,unveiled [13] unveiled,amazon [13] amazon,biggest [13] biggest,push [13] push,selling [13] drugs,launch Top Word Pairs in Tweet in G8:
[40] digital,divide [40] divide,crucial [40] crucial,reduce [40] reduce,health [37] three,year [37] year,project [37] project,trialling [37] trialling,digital [37] digital,technology [37] technology,shows Top Word Pairs in Tweet in G9:
[60] digital,health [40] landscape,report [31] center,digital [29] stanford,center [26] health,landscape [25] first,kind [23] cdh,excited [23] excited,announce [23] announce,release [23] release,stanford Top Word Pairs in Tweet in G10:
[15] digital,health [9] learn,more [9] founder,ceo [7] #digitalhealth,#healthcare [7] #digitalhealth,week [6] paper,webmap [6] webmap,mobile [6] mobile,editor's [6] editor's,choice [6] choice,list 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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