The graph represents a network of 1,322 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, 02 December 2022 at 03:22 UTC.
The requested start date was Friday, 02 December 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 121-day, 13-hour, 30-minute period from Monday, 01 August 2022 at 02:34 UTC to Wednesday, 30 November 2022 at 16:05 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 : 1322
Unique Edges : 1052
Edges With Duplicates : 3275
Total Edges : 4327
Number of Edge Types : 5
Retweet : 1171
MentionsInRetweet : 1813
Mentions : 785
Tweet : 519
Replies to : 39
Self-Loops : 535
Reciprocated Vertex Pair Ratio : 0.0636904761904762
Reciprocated Edge Ratio : 0.119753777280358
Connected Components : 214
Single-Vertex Connected Components : 103
Maximum Vertices in a Connected Component : 787
Maximum Edges in a Connected Component : 3430
Maximum Geodesic Distance (Diameter) : 11
Average Geodesic Distance : 4.413047
Graph Density : 0.00102327008947744
Modularity : 0.380023
NodeXL Version : 1.0.1.508
Data Import : The graph represents a network of 1,322 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, 02 December 2022 at 03:22 UTC.
The requested start date was Friday, 02 December 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 121-day, 13-hour, 30-minute period from Monday, 01 August 2022 at 02:34 UTC to Wednesday, 30 November 2022 at 16:05 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:
[137] #digitalhealth,#personalizedmedicine [87] #meded,#telemednow [83] #telemednow,#capchat [80] #personalizedmedicine,#patientsafety [79] personalized,medicine [76] #healthcareai,#smarthit [76] #smarthit,#imagingai [75] #personalizedmedicine,#bigdata [72] #globalhealth,#meded [72] publichealthbot,#publichealth Top Word Pairs in Tweet in G1:
[133] #digitalhealth,#personalizedmedicine [82] #meded,#telemednow [80] #personalizedmedicine,#patientsafety [78] #telemednow,#capchat [73] #smarthit,#imagingai [73] #healthcareai,#smarthit [72] publichealthbot,#publichealth [71] #personalizedmedicine,#bigdata [70] #publichealth,#datascience [68] #globalhealth,#meded Top Word Pairs in Tweet in G2:
[11] personalized,medicine [6] #precisionmedicine,#personalizedmedicine [5] #custommedications,#personalizedmedicine [5] #compounding,#custommedications [4] #hormonereplacementtherapy,#hormonereplacement [4] learn,more [4] #womenshealthandwellness,#hormonereplacementtherapy [4] #personalizedmedicine,#precisionmedicine [4] #hormonereplacement,#compounding [3] #womenshealth,#womenshealthandwellness Top Word Pairs in Tweet in G3:
[11] read,more [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 Top Word Pairs in Tweet in G4:
[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 G5:
[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 G6:
[8] dr,julie [8] ceo,dr [8] julie,rosser [7] javlemilind,mdandersonnews [7] mdandersonnews,providing [7] updates,#cholangiocarcinoma [7] right,javlemilind [7] #cholangiocarcinoma,greatdebatescme [7] greatdebatescme,#gdugi2022 [7] providing,updates Top Word Pairs in Tweet in G7:
[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 G8:
[3] genetic,profile [3] awareness,month [3] month,pm [3] #personalizedmedicine,awareness [3] guide,decisions [3] pm,uses [3] november,#personalizedmedicine [3] decisions,made [3] profile,guide [3] individual's,genetic Top Word Pairs in Tweet in G9:
[9] pm,learn [9] engineering,follow [9] nov,16 [9] learn,ms [9] 16,pm [9] personalized,medicine [9] ms,personalized [9] applied,engineering [9] join,wed [9] medicine,applied Top Word Pairs in Tweet in G10:
[8] bring,forward [8] health,data [8] research,hospitals [8] forward,#personalizedmedicine [8] actors,research [8] #personalizedmedicine,decisively [8] high,quality [8] quality,health [8] decisively,actors [8] data,bring Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G3:
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Top Replied-To in G5:
Top Replied-To in G8:
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 G8:
Top Tweeters in G9:
Top Tweeters in G10: