The graph represents a network of 3,741 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, 31 July 2020 at 22:49 UTC.
The requested start date was Friday, 31 July 2020 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 4-day, 13-hour, 30-minute period from Saturday, 25 July 2020 at 15:16 UTC to Thursday, 30 July 2020 at 04:46 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 : 3741
Unique Edges : 3870
Edges With Duplicates : 7620
Total Edges : 11490
Number of Edge Types : 5
Mentions : 2384
Tweet : 1431
Retweet : 2893
MentionsInRetweet : 4713
Replies to : 69
Self-Loops : 1536
Reciprocated Vertex Pair Ratio : 0.0438580527752502
Reciprocated Edge Ratio : 0.0840306834030683
Connected Components : 562
Single-Vertex Connected Components : 297
Maximum Vertices in a Connected Component : 2497
Maximum Edges in a Connected Component : 9526
Maximum Geodesic Distance (Diameter) : 16
Average Geodesic Distance : 5.433486
Graph Density : 0.000409967880131567
Modularity : 0.451738
NodeXL Version : 1.0.1.439
Data Import : The graph represents a network of 3,741 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, 31 July 2020 at 22:49 UTC.
The requested start date was Friday, 31 July 2020 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 4-day, 13-hour, 30-minute period from Saturday, 25 July 2020 at 15:16 UTC to Thursday, 30 July 2020 at 04:46 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:
[541] gt,gt [306] digital,health [276] covid,19 [269] #healthtech,#digitalhealth [185] read,more [184] retweet,#arrestbillgates [181] gt,#digitalhealth [160] #digitalhealth,#healthcare [146] #digitalmarketing,#bigdata [142] #bigdata,#startups Top Word Pairs in Tweet in G1:
[484] gt,gt [167] gt,#digitalhealth [123] #digitalhealth,#socialmedia [115] #digitalhealth,#healthcare [113] #mhealth,#digitalhealth [112] read,more [109] more,#cure [109] #cure,#digitalhealth [107] #telemedicine,#telehealth [107] #healthcare,#infographic Top Word Pairs in Tweet in G2:
[176] #healthtech,#digitalhealth [125] ty,seeker [61] #digitalhealth,#ai [56] #wearables,#iot [53] sensor,patch [53] patch,heals [53] heals,injuries [53] injuries,artfully [53] artfully,ty [53] seeker,#wearables Top Word Pairs in Tweet in G3:
[34] digital,health [30] covid,19 [20] #covid,19 [18] #digitalhealth,#insights [17] #esante,#hcsmeufr [17] #hcsmeufr,#digitalhealth [16] learn,more [16] #digitalhealth,#coronavirus [16] #coronavirus,#covid [16] 19,#covid19fr Top Word Pairs in Tweet in G4:
[24] find,recommend [19] recommend,assessed [17] read,more [16] assessed,apps [15] digital,health [13] webinar,find [12] health,informatics [12] 31,july [12] full,story [12] covid,19 Top Word Pairs in Tweet in G5:
[25] timeline,emerging [25] emerging,science [25] science,technology [25] technology,full [25] full,rez [25] rez,pdf [25] pdf,#robotics [24] #robotics,#nanotech [24] #nanotech,#ai [24] kirkdborne,timeline Top Word Pairs in Tweet in G6:
[15] health,care [14] covid,19 [11] interesting,read [11] 19,pandemic [11] user,testing [10] read,mayoclinic [10] mayoclinic,strategies [10] strategies,#covid19 [10] #covid19,health [10] care,covid Top Word Pairs in Tweet in G7:
[120] #digitalmarketing,#bigdata [116] #bigdata,#startups [109] #startups,#startup [58] presentation,template [58] template,#digitalmarketing [49] sprite4it,best [37] #startup,#digitalhealth [37] #contentmarketing,#marketing [37] #datascience,#ai [37] #ai,#5g Top Word Pairs in Tweet in G8:
[35] healthcare,sectors [35] sectors,build [35] build,#digitaltech [35] #covid19,response [33] undp,healthcare [29] #digitaltech,infrastructure [29] infrastructure,#covid19 [29] response,moment [29] moment,establish [29] establish,sustainable Top Word Pairs in Tweet in G9:
[9] covid,19 [5] validic,joining [5] talk,#digitalhealth [5] management,exchange [4] joining,talk [4] #digitalhealth,data [4] data,management [4] exchange,connected [4] connected,care [4] care,more Top Word Pairs in Tweet in G10:
[174] retweet,#arrestbillgates [129] hashtag,time [113] please,retweet [61] kindly,retweet [58] drunkalexjones,hey [38] time,#fishingforrobots [38] #fishingforrobots,#eventi [38] #eventi,#trenroca [32] transylvania,please [26] #arrestbillgates,nonsensical 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: