The graph represents a network of 1,886 Twitter users whose tweets in the requested range contained "HealthIT", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Tuesday, 16 November 2021 at 18:01 UTC.
The requested start date was Tuesday, 16 November 2021 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 13-day, 23-hour, 29-minute period from Tuesday, 02 November 2021 at 01:30 UTC to Tuesday, 16 November 2021 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 : 1886
Unique Edges : 1770
Edges With Duplicates : 6622
Total Edges : 8392
Number of Edge Types : 5
Tweet : 1178
MentionsInRetweet : 3058
Mentions : 1818
Retweet : 2210
Replies to : 128
Self-Loops : 1282
Reciprocated Vertex Pair Ratio : 0.0502008032128514
Reciprocated Edge Ratio : 0.0956022944550669
Connected Components : 209
Single-Vertex Connected Components : 108
Maximum Vertices in a Connected Component : 1439
Maximum Edges in a Connected Component : 7602
Maximum Geodesic Distance (Diameter) : 11
Average Geodesic Distance : 4.72196
Graph Density : 0.000882673109974094
Modularity : 0.323438
NodeXL Version : 1.0.1.447
Data Import : The graph represents a network of 1,886 Twitter users whose tweets in the requested range contained "HealthIT", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Tuesday, 16 November 2021 at 18:01 UTC.
The requested start date was Tuesday, 16 November 2021 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 13-day, 23-hour, 29-minute period from Tuesday, 02 November 2021 at 01:30 UTC to Tuesday, 16 November 2021 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 : HealthIT
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:
[516] #rstats,#reactjs [508] #machinelearning,#ai [499] #reactjs,#iot [480] #iot,#iiot [399] #analytics,#machinelearning [399] #iiot,#ml [269] #ai,#python [269] #python,#rstats [244] #ai,#rstats [241] #ml,#nlp Top Word Pairs in Tweet in G1:
[21] #hl7,#fhir [21] health,care [19] learn,more [18] onc_healthit,#hitac [17] amalec,onc_healthit [16] #healthit,#interoperability [14] mandl,aneeshchopra [14] aneeshchopra,dmccallie [14] dmccallie,rickybloomfield [13] onc_healthit,recently Top Word Pairs in Tweet in G2:
[98] digital,health [84] #ehealth,#healthit [62] wearablesexpert,talks [61] #healthit,#digitalhealth [49] #digitalhealth,#ehealth [47] use,digital [41] #43,wearablesexpert [41] talks,_atanas_ [41] _atanas_,social [41] social,media Top Word Pairs in Tweet in G3:
[492] #rstats,#reactjs [484] #machinelearning,#ai [477] #reactjs,#iot [442] #iot,#iiot [382] #iiot,#ml [379] #analytics,#machinelearning [258] #ai,#python [258] #python,#rstats [232] #ai,#rstats [230] #ml,#nlp Top Word Pairs in Tweet in G4:
[92] starts,listen [92] listen,live [37] healthcare,today [31] john,lynn [30] tate,chronicles [30] host,jim [30] jim,tate [30] #healthit,starts [23] colin,hung [22] leading,edge Top Word Pairs in Tweet in G5:
[46] #healthit,#cybersecurity [43] #cybersecurity,#infosec [36] incident,response [30] motivated,wannacry [30] wannacry,attack [30] attack,group [30] group,unveils [30] unveils,medical [30] medical,device [30] device,incident Top Word Pairs in Tweet in G6:
[48] learn,more [48] net,health [22] link,below [21] dallas,stop [21] stop,exhibit [21] exhibit,ask [21] ask,net [21] health,therapy [21] therapy,outpatient [21] outpatient,help Top Word Pairs in Tweet in G7:
[26] connection,november [26] 2021,mihin [19] #healthit,#hit [17] mihin,#healthit [13] #hit,#ai [11] health,tech [11] tech,news [11] news,today [11] today,thanks [10] himss,changemaker Top Word Pairs in Tweet in G8:
[100] #healthit,#healthcareit [96] #healthcareit,#informatics [51] #informatics,#technology [48] #healthcare,#healthit [45] #informatics,#news [34] #technology,#healthit [32] #healthcare,#healthtech [32] #informatics,#healthcare [32] #healthcare,#healthcareit [32] #healthcareit,#technology Top Word Pairs in Tweet in G9:
[21] fall,forum [16] #healthimpact,#healthimpactfall [15] live,fall [11] healthimpact,live [9] 30,pm [9] #healthimpact,#healthit [9] meet,speakers [8] virtual,booth [8] michael,ames [8] ames,sada Top Word Pairs in Tweet in G10:
[20] hey,looking [20] looking,women [20] women,executives [20] executives,healthcare [20] healthcare,vendors [20] vendors,medtech [20] medtech,companies [20] companies,bring [20] bring,podcast [19] mmsjennifer,hey 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: