The graph represents a network of 2,040 Twitter users whose tweets in the requested range contained "hemophilia OR haemophilia OR bleedingdisorders OR hemochat ", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Monday, 06 May 2019 at 16:47 UTC.
The requested start date was Monday, 06 May 2019 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 13-day, 23-hour, 52-minute period from Monday, 22 April 2019 at 00:01 UTC to Sunday, 05 May 2019 at 23:54 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 : 2040
Unique Edges : 2398
Edges With Duplicates : 1066
Total Edges : 3464
Number of Edge Types : 3
Mentions : 2438
Tweet : 863
Replies to : 163
Self-Loops : 863
Reciprocated Vertex Pair Ratio : 0.0260829063809967
Reciprocated Edge Ratio : 0.0508397639582388
Connected Components : 546
Single-Vertex Connected Components : 324
Maximum Vertices in a Connected Component : 873
Maximum Edges in a Connected Component : 2027
Maximum Geodesic Distance (Diameter) : 15
Average Geodesic Distance : 6.056444
Graph Density : 0.000529623325544048
Modularity : 0.628645
NodeXL Version : 1.0.1.412
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[125] infected,blood [122] brain,injury [120] haemophilia,brain [119] born,aus [119] aus,haemophilia [119] injury,sort [119] sort,minister [119] minister,government [119] government,department [119] department,send Top Word Pairs in Tweet in G1:
[93] ã,ã [35] ì,ì [33] ë,ì [25] ì,í [20] gene,therapy [18] ì,ë [16] contaminated,blood [16] #hemophilia,#vwd [15] ã,è [14] hemophilia,b Top Word Pairs in Tweet in G2:
[111] infected,blood [67] blood,inquiry [54] contaminated,blood [46] #contaminatedblood,#haemophilia [38] #infectedbloodinquiry,#contaminatedblood [38] blood,scandal [33] public,inquiry [32] blood,public [32] public,hearings [32] haemosocuk,member Top Word Pairs in Tweet in G3:
[33] world,hemophilia [32] hemophilia,day [27] proud,part [23] bleeding,disorders [22] 4,weeks [21] persons,#hemophilia [20] emicizumab,one [20] one,dose [20] dose,4 [20] s,clinically Top Word Pairs in Tweet in G4:
[114] born,aus [114] aus,haemophilia [114] haemophilia,brain [114] brain,injury [114] injury,sort [114] sort,minister [114] minister,government [114] government,department [114] department,send [114] send,child Top Word Pairs in Tweet in G5:
[27] gene,therapy [18] 9,things [18] things,know [17] hemophilia,gene [15] biomarin,s [15] s,hemophilia [15] therapy,faces [15] faces,crucial [15] crucial,durability [15] durability,test Top Word Pairs in Tweet in G6:
[14] bleeding,disorders [7] people,bleeding [7] hemophilia,b [6] help,people [6] #press,novo [6] novo,nordisk [6] nordisk,receives [6] receives,positive [6] positive,opinion [6] opinion,european Top Word Pairs in Tweet in G8:
[43] hey,peterdutton_mp [43] peterdutton_mp,come [43] come,office [43] office,find [43] find,compelling [43] compelling,reason [43] reason,compassionate [43] compassionate,reason [42] ifearforfuture,hey [6] haemophilia,brain Top Word Pairs in Tweet in G9:
[31] 문재인,정부 [31] 정부,국정과제인 [31] 국정과제인,지속가능한 [31] 지속가능한,국토환경 [31] 국토환경,조성 [31] 조성,의 [31] 의,일환으로 [31] 일환으로,생태계서비스의 [31] 생태계서비스의,개념을 [31] 개념을,정의하고 Top Word Pairs in Tweet in G10:
[4] severe,haemophilia [4] #repost,rouleurmagazine [4] rouleurmagazine,get_repost [4] get_repost,haemophilia [4] haemophilia,isn [4] isn,t [4] t,blood [4] blood,thickening [4] thickening,thinning [4] thinning,s Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Replied-To in G5:
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Top Replied-To in G7:
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 G7:
Top Mentioned in G8:
Top Mentioned in G9:
Top Mentioned in G10:
Top Tweeters in Entire Graph:
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Top Tweeters in G10: