The graph represents a network of 1,261 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, 25 November 2022 at 03:22 UTC.
The requested start date was Friday, 25 November 2022 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 114-day, 1-hour, 4-minute period from Monday, 01 August 2022 at 02:34 UTC to Wednesday, 23 November 2022 at 03:39 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 : 1261
Unique Edges : 998
Edges With Duplicates : 3155
Total Edges : 4153
Number of Edge Types : 5
Mentions : 760
Tweet : 485
Retweet : 1125
MentionsInRetweet : 1744
Replies to : 39
Self-Loops : 501
Reciprocated Vertex Pair Ratio : 0.0630797773654917
Reciprocated Edge Ratio : 0.118673647469459
Connected Components : 194
Single-Vertex Connected Components : 89
Maximum Vertices in a Connected Component : 762
Maximum Edges in a Connected Component : 3332
Maximum Geodesic Distance (Diameter) : 10
Average Geodesic Distance : 4.343537
Graph Density : 0.00108190778293871
Modularity : 0.377929
NodeXL Version : 1.0.1.508
Data Import : The graph represents a network of 1,261 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, 25 November 2022 at 03:22 UTC.
The requested start date was Friday, 25 November 2022 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 114-day, 1-hour, 4-minute period from Monday, 01 August 2022 at 02:34 UTC to Wednesday, 23 November 2022 at 03:39 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:
[135] #digitalhealth,#personalizedmedicine [87] #meded,#telemednow [83] #telemednow,#capchat [78] #personalizedmedicine,#patientsafety [76] #healthcareai,#smarthit [76] #smarthit,#imagingai [75] #personalizedmedicine,#bigdata [72] personalized,medicine [72] #globalhealth,#meded [71] #artificialintelligence,#machinelearning Top Word Pairs in Tweet in G1:
[131] #digitalhealth,#personalizedmedicine [82] #meded,#telemednow [78] #personalizedmedicine,#patientsafety [78] #telemednow,#capchat [73] #smarthit,#imagingai [73] #healthcareai,#smarthit [71] #personalizedmedicine,#bigdata [70] publichealthbot,#publichealth [68] #globalhealth,#meded [68] #publichealth,#datascience Top Word Pairs in Tweet in G2:
[8] personalized,medicine [5] #precisionmedicine,#personalizedmedicine [4] #custommedications,#personalizedmedicine [4] #compounding,#custommedications [4] learn,more [3] cutting,edge [3] cancer,treatment [3] #hormonereplacementtherapy,#hormonereplacement [3] #personalizedmedicine,#oncology [3] read,more Top Word Pairs in Tweet in G3:
[26] psma,imaging [21] profkherrmann,drmhofman [21] #prostatecancer,profkherrmann [21] elila74,stefanofanti4 [21] metastatic,#prostatecancer [21] role,psma [21] drmhofman,elila74 [21] imaging,metastatic [20] journalofnucmed,role [14] radiopharmaceutical,therapy Top Word Pairs in Tweet in G4:
[11] personalized,medicine [10] #personalizedmedicine,#precisionhealth [10] discussed,needed [10] needed,move [10] permedcoalition,conference [10] pmc,today [10] #precisionhealth,forward [10] move,#personalizedmedicine [10] conference,discussed [9] dramyabernethy,permedcoalition Top Word Pairs in Tweet in G5:
[11] read,more [5] #genomics,revolutionizing [5] more,#healthcare [5] disease,severity [5] explain,#genomics [5] #covid19,disease [5] infographic,#understandgenomics [5] human,health [5] revolutionizing,human [5] #understandgenomics,series Top Word Pairs in Tweet in G6:
[8] ceo,dr [8] julie,rosser [8] dr,julie [7] right,javlemilind [7] #cholangiocarcinoma,greatdebatescme [7] greatdebatescme,#gdugi2022 [7] updates,#cholangiocarcinoma [7] providing,updates [7] mdandersonnews,providing [7] javlemilind,mdandersonnews Top Word Pairs in Tweet in G7:
[9] ferrari,alberta [9] 25,2022 [9] bioaro's,launch [9] met,number [9] event,thankful [9] 24,25 [9] thank,ferrari [9] number,life [9] hosting,bioaro's [9] launch,event Top Word Pairs in Tweet in G8:
[15] special,issue [14] issue,introduces [12] thehdsr,special [8] introduces,personalized [8] fascinating,paper [8] paper,issue [8] science,scientific [8] data,science [8] investigation,individual [8] personalized,data Top Word Pairs in Tweet in G9:
[2] #somaticepitype,#personalizedmedicine [2] basic,role [2] discussion,support [2] join,discussion [2] support,implementation [2] implementation,#personalizedmedicine [2] genome_gov,elonmusk [2] symptoms,immediacy [2] cause,needs [2] role,government Top Word Pairs in Tweet in G10:
[8] pm,learn [8] engineering,follow [8] nov,16 [8] learn,ms [8] 16,pm [8] personalized,medicine [8] ms,personalized [8] applied,engineering [8] join,wed [8] medicine,applied Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G3:
Top Replied-To in G4:
Top Replied-To in G5:
Top Replied-To in G9:
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: