The graph represents a network of 1,122 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, 28 May 2021 at 02:45 UTC.
The requested start date was Friday, 28 May 2021 at 00:01 UTC and the maximum number of tweets (going backward in time) was 7,500.
The tweets in the network were tweeted over the 86-day, 16-hour, 47-minute period from Monday, 01 March 2021 at 02:15 UTC to Wednesday, 26 May 2021 at 19:02 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 : 1122
Unique Edges : 803
Edges With Duplicates : 2337
Total Edges : 3140
Number of Edge Types : 5
Retweet : 900
MentionsInRetweet : 1220
Tweet : 559
Mentions : 439
Replies to : 22
Self-Loops : 636
Reciprocated Vertex Pair Ratio : 0.0524590163934426
Reciprocated Edge Ratio : 0.0996884735202492
Connected Components : 240
Single-Vertex Connected Components : 105
Maximum Vertices in a Connected Component : 405
Maximum Edges in a Connected Component : 1892
Maximum Geodesic Distance (Diameter) : 17
Average Geodesic Distance : 6.069713
Graph Density : 0.00102086086238891
Modularity : 0.407021
NodeXL Version : 1.0.1.445
Data Import : The graph represents a network of 1,122 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, 28 May 2021 at 02:45 UTC.
The requested start date was Friday, 28 May 2021 at 00:01 UTC and the maximum number of tweets (going backward in time) was 7,500.
The tweets in the network were tweeted over the 86-day, 16-hour, 47-minute period from Monday, 01 March 2021 at 02:15 UTC to Wednesday, 26 May 2021 at 19:02 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:
[195] add'l,biozhena [166] #impinv,#vc [165] #precisionmedicine,#digitalmedicine [165] #digitalmedicine,#personalizedmedicine [163] #fertility,#precisionmedicine [162] #vc,#obgyn [158] #ehealth,#impinv [156] biozhena,files [150] #personalizedmedicine,#womenshealth [148] #emergingtech,#fertility Top Word Pairs in Tweet in G1:
[12] best,approaches [12] approaches,technologies [12] technologies,producing [12] producing,#personalizedmedicine [12] #personalizedmedicine,fight [12] fight,cancer [12] cancer,rare [12] rare,diseases [12] diseases,ebook [12] ebook,looks Top Word Pairs in Tweet in G2:
[80] analyse,twistbioscience [80] twistbioscience,whole [80] whole,exome [80] exome,sequencing [80] sequencing,kit [80] kit,fully [80] fully,automated [80] automated,seamless [80] seamless,ngs [80] ngs,platform Top Word Pairs in Tweet in G3:
[10] awesome,interview [10] interview,jeremyjbarr [10] jeremyjbarr,#bacteriophages [10] #bacteriophages,we_talk_science [10] we_talk_science,phages [10] phages,being [10] being,utilized [10] utilized,solve [10] solve,issues [9] shebaaj,awesome Top Word Pairs in Tweet in G4:
[22] #digitalhealth,#personalizedmedicine [20] story,behind [20] behind,#dhpsp [20] #dhpsp,creation [20] creation,highlighted [20] highlighted,interview [20] interview,_atanas_ [20] _atanas_,s_jungmann [20] s_jungmann,#digitalhealth [19] dhpsp,story Top Word Pairs in Tweet in G5:
[15] anyone,opining [15] opining,biomarkers [15] biomarkers,firm [14] bible,read [14] read,each [14] each,sunday [14] sunday,publication [14] publication,anyone [13] doccatenacci,bible [13] firm,understand Top Word Pairs in Tweet in G6:
[13] ensure,#patient [13] #patient,safety [13] safety,brand [13] brand,protection [13] protection,supporting [13] supporting,#personalizedmedicine [13] #personalizedmedicine,segments [13] segments,one [8] video,available [8] available,discover Top Word Pairs in Tweet in G7:
[6] inclusive,research [4] covid,19 [3] begin,prioritize [3] prioritize,health [3] health,care [3] care,issues [3] issues,directly [3] directly,related [3] related,covid [3] 19,political Top Word Pairs in Tweet in G8:
[10] #gograyinmay,#maygray [10] #maygray,#brain [10] #brain,#braintumor [10] #braintumor,#braincancer [10] #braincancer,#braincancerresearch [10] #braincancerresearch,#braincancerawareness [10] #braincancerawareness,#clinicaltrials [10] #clinicaltrials,#glioma [8] read,full [8] full,story Top Word Pairs in Tweet in G9:
[17] #personalizedmedicine,#personalizedhealthcare [14] #healthlynked,#personalizedmedicine [13] #personalizedhealthcare,#customizedmedicine [11] #ai,#artificialintelligence [10] artificial,intelligence [10] #digitalhealth,#ehealth [9] #customizedmedicine,#digitalhealth [7] #genes,cause [7] cause,#cancer [6] #machinelearning,#deeplearning Top Word Pairs in Tweet in G10:
[18] fbn1,#genotypephenotype [18] #genotypephenotype,correlations [18] correlations,#aortic [18] #aortic,extra [18] extra,aortic [18] aortic,features [18] features,#marfan [18] #marfan,better [18] better,#riskstratification [17] judbacke,fbn1 Top Replied-To in Entire Graph:
Top Replied-To in G2:
Top Replied-To in G5:
Top Replied-To in G8:
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 G7:
Top Mentioned in G8:
Top Mentioned in G9:
Top Mentioned in G10:
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: