The graph represents a network of 1,176 Twitter users whose tweets in the requested range contained "personalizedmedicine", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 10 December 2021 at 04:04 UTC.
The requested start date was Friday, 10 December 2021 at 01:01 UTC and the maximum number of tweets (going backward in time) was 7,500.
The tweets in the network were tweeted over the 67-day, 12-hour, 28-minute period from Friday, 01 October 2021 at 08:37 UTC to Tuesday, 07 December 2021 at 21:05 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 : 1176
Unique Edges : 986
Edges With Duplicates : 2033
Total Edges : 3019
Number of Edge Types : 5
Tweet : 310
Retweet : 850
MentionsInRetweet : 1378
Mentions : 465
Replies to : 16
Self-Loops : 371
Reciprocated Vertex Pair Ratio : 0.0538563829787234
Reciprocated Edge Ratio : 0.102208201892744
Connected Components : 199
Single-Vertex Connected Components : 77
Maximum Vertices in a Connected Component : 377
Maximum Edges in a Connected Component : 1383
Maximum Geodesic Distance (Diameter) : 17
Average Geodesic Distance : 5.796842
Graph Density : 0.00114705456650745
Modularity : 0.5084
NodeXL Version : 1.0.1.447
Data Import : The graph represents a network of 1,176 Twitter users whose tweets in the requested range contained "personalizedmedicine", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 10 December 2021 at 04:04 UTC.
The requested start date was Friday, 10 December 2021 at 01:01 UTC and the maximum number of tweets (going backward in time) was 7,500.
The tweets in the network were tweeted over the 67-day, 12-hour, 28-minute period from Friday, 01 October 2021 at 08:37 UTC to Tuesday, 07 December 2021 at 21:05 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 : personalizedmedicine
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:
[123] ai,transforming [123] transforming,healthcare [123] healthcare,those [123] those,changes [123] changes,happening [123] happening,inside [121] drgauravchandra,ai [119] inside,microbiome [119] microbiome,level [113] level,tak Top Word Pairs in Tweet in G1:
[122] ai,transforming [122] transforming,healthcare [122] healthcare,those [122] those,changes [122] changes,happening [122] happening,inside [121] drgauravchandra,ai [118] inside,microbiome [118] microbiome,level [113] level,tak Top Word Pairs in Tweet in G2:
[43] î,î [23] #personalizedmedicine,call [13] learn,more [12] visit,website [11] call,today [8] health,#personalizedmedicine [8] today,find [7] wondering,#personalizedmedicine [7] call,visit [7] website,find Top Word Pairs in Tweet in G3:
[23] #healthcareai,#smarthit [18] #redaichat,#isaml [18] #isaml,#healthcareai [18] #personalizedmedicine,#bigdata [18] digital,health [15] #bigdata,#analytics [15] impacts,biomedical [15] biomedical,hashtag [15] hashtag,based [15] based,twitter Top Word Pairs in Tweet in G4:
[46] analyse,twistbioscience [46] twistbioscience,whole [46] whole,exome [46] exome,sequencing [46] sequencing,kit [46] kit,fully [46] fully,automated [46] automated,seamless [46] seamless,ngs [46] ngs,platform Top Word Pairs in Tweet in G5:
[31] science,health [29] data,science [28] #personalizedmedicine,#sfh2021 [19] #ai,#bigdata [18] learn,more [18] #datascience,#ai [17] #event,#personalizedmedicine [16] #bigdata,#healthcare [16] #healthcare,#event [13] health,2021 Top Word Pairs in Tweet in G6:
[19] jbarbosapr,enricomolinari [19] enricomolinari,raconteur [19] raconteur,evankirstel [19] evankirstel,johnnosta [19] johnnosta,jolaburnett [19] jolaburnett,michelleragusa [19] michelleragusa,tylercohenwood [19] tylercohenwood,trippbraden [18] irmaraste,jbarbosapr [18] trippbraden,ra Top Word Pairs in Tweet in G7:
[8] #bioengineering,#drugdesign [8] #drugdesign,#bioinformatics [8] #bioinformatics,researchers [8] researchers,developed [8] developed,machine [8] machine,learning [8] learning,based [8] based,computational [8] computational,method [7] gang,song Top Word Pairs in Tweet in G8:
[7] advances,#personalizedmedicine [6] pandemic's,tragically [6] tragically,uneven [6] uneven,impact [6] latest,article [6] article,permedcoalition [6] permedcoalition,discuss [6] discuss,potential [6] potential,exciting [6] exciting,advances Top Word Pairs in Tweet in G9:
[8] #biobanking,provides [8] provides,fundamental [8] fundamental,infrastructure [8] infrastructure,#personalizedmedicine [8] #personalizedmedicine,prevention [8] prevention,diagnostics [8] diagnostics,treatment [7] bbmrieric,#biobanking [6] #fh,#bestpractice [6] #bestpractice,#personalizedmedicine Top Word Pairs in Tweet in G10:
[26] early,stage [26] stage,researcher [25] tipat,early [19] #tipat,#amr [19] #amr,#personalizedmedicine [14] free,time [8] #personalizedmedicine,mscactions [7] researcher,uppsala [7] uppsala,university [7] university,uu_university Top Replied-To in Entire Graph:
Top Replied-To in G2:
Top Replied-To in G3:
Top Replied-To in G4:
Top Replied-To in G6:
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Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Mentioned in G10:
Top Tweeters in Entire Graph:
Top Tweeters in G1:
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Top Tweeters in G5:
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Top Tweeters in G9:
Top Tweeters in G10: