The graph represents a network of 289 Twitter users whose recent tweets contained "#xMed", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 18,000 tweets. The network was obtained from Twitter on Friday, 01 November 2019 at 13:44 UTC.
The tweets in the network were tweeted over the 8-day, 21-hour, 8-minute period from Wednesday, 23 October 2019 at 16:30 UTC to Friday, 01 November 2019 at 13:38 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 : 289
Unique Edges : 787
Edges With Duplicates : 238
Total Edges : 1025
Self-Loops : 27
Reciprocated Vertex Pair Ratio : 0.0393120393120393
Reciprocated Edge Ratio : 0.0756501182033097
Connected Components : 3
Single-Vertex Connected Components : 0
Maximum Vertices in a Connected Component : 284
Maximum Edges in a Connected Component : 1021
Maximum Geodesic Distance (Diameter) : 5
Average Geodesic Distance : 2.818927
Graph Density : 0.0101643598615917
Modularity : 0.484523
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 289 Twitter users whose recent tweets contained "#xMed", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 18,000 tweets. The network was obtained from Twitter on Friday, 01 November 2019 at 13:44 UTC.
The tweets in the network were tweeted over the 8-day, 21-hour, 8-minute period from Wednesday, 23 October 2019 at 16:30 UTC to Friday, 01 November 2019 at 13:38 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 : TwitterSearch
Graph Term : #xMed
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 : Followers
Vertex Alpha : Followers
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[68] #hlth2019,#xmed [55] #xmed,#radiology [53] mri,20x [53] 20x,less [53] less,costly [53] costly,build [53] build,10x [53] 10x,lighter [53] lighter,uses [53] uses,35x Top Word Pairs in Tweet in G1:
[47] mri,20x [47] 20x,less [47] less,costly [47] costly,build [47] build,10x [47] 10x,lighter [47] lighter,uses [47] uses,35x [47] 35x,less [47] less,power Top Word Pairs in Tweet in G2:
[32] #hlth2019,#xmed [31] excited,start [31] start,process [31] process,exploring [31] exploring,new [31] new,synergies [31] synergies,medical [31] medical,education [31] education,simulation [31] simulation,innovation Top Word Pairs in Tweet in G3:
[28] 12,innovations [27] innovations,change [27] change,#healthcare [27] #healthcare,2020s [27] 2020s,#drones [27] #drones,#bigdata [27] #bigdata,#biobanks [27] #biobanks,#immunotherapy [27] #immunotherapy,#ai [27] #ai,#mobiledx Top Word Pairs in Tweet in G4:
[11] #hcsmzw,#hcsmafrica [11] 4,7 [10] nov,4 [10] san,diego [9] join,next [9] next,week [9] robot,assist [9] assist,surgeon [9] surgeon,now [8] digital,technologies Top Word Pairs in Tweet in G5:
[17] #hlth2019,#xmed [16] #xmed,#jpm20 [7] former,deptvetaffairs [7] deptvetaffairs,secretary [7] secretary,davidshulkin [5] headsup,disruptors [5] disruptors,transformers [5] transformers,#digitalhealth [5] #digitalhealth,evangelists [5] evangelists,#tripleaim Top Word Pairs in Tweet in G6:
[15] exponentialmed,#pinksocks [12] super,stoked [12] stoked,#xmed [12] #xmed,calendar [12] calendar,again [12] again,year [12] year,5th [12] 5th,exponentialmed [12] #pinksocks,smiles [12] smiles,hugs Top Word Pairs in Tweet in G7:
[8] #xmed,wonderful [8] wonderful,event [8] event,attend [8] attend,one [8] one,inspired [8] inspired,cutting [8] cutting,edge [8] edge,technology [8] technology,put [8] put,practice Top Word Pairs in Tweet in G8:
[6] excited,start [6] start,process [6] process,exploring [6] exploring,new [6] new,synergies [6] synergies,medical [6] medical,education [6] education,simulation [6] simulation,innovation [6] innovation,training Top Word Pairs in Tweet in G9:
[2] check,out [2] out,meetup [2] meetup,a360 [2] a360,collaboration [2] collaboration,singularityu [2] singularityu,san [2] san,diego [2] diego,chapter [2] chapter,event [2] event,#xmed Top Word Pairs in Tweet in G10:
[2] value,healthcare Top Replied-To in Entire Graph:
Top Replied-To in G2:
Top Replied-To in G4:
Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
Top Mentioned in G2:
Top Mentioned in G3:
Top Mentioned in G4:
Top Mentioned in G5:
Top Mentioned in G6:
Top Mentioned in G8:
Top Mentioned in G9:
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: