The graph represents a network of 1,805 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 Tuesday, 22 June 2021 at 15:36 UTC.
The requested start date was Tuesday, 22 June 2021 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 7,500.
The tweets in the network were tweeted over the 13-day, 23-hour, 10-minute period from Tuesday, 08 June 2021 at 00:47 UTC to Monday, 21 June 2021 at 23:58 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 : 1805
Unique Edges : 1025
Edges With Duplicates : 3487
Total Edges : 4512
Number of Edge Types : 5
Retweet : 1168
MentionsInRetweet : 1417
Mentions : 1059
Replies to : 205
Tweet : 663
Self-Loops : 676
Reciprocated Vertex Pair Ratio : 0.0251778872468528
Reciprocated Edge Ratio : 0.0491190603310198
Connected Components : 410
Single-Vertex Connected Components : 186
Maximum Vertices in a Connected Component : 566
Maximum Edges in a Connected Component : 2627
Maximum Geodesic Distance (Diameter) : 13
Average Geodesic Distance : 4.899698
Graph Density : 0.000575206834919017
Modularity : 0.420163
NodeXL Version : 1.0.1.445
Data Import : The graph represents a network of 1,805 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 Tuesday, 22 June 2021 at 15:36 UTC.
The requested start date was Tuesday, 22 June 2021 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 7,500.
The tweets in the network were tweeted over the 13-day, 23-hour, 10-minute period from Tuesday, 08 June 2021 at 00:47 UTC to Monday, 21 June 2021 at 23:58 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 : hemophilia OR haemophilia OR bleedingdisorders OR hemochat
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:
[102] diseases,including [101] mystical,ancient [101] ancient,simple [101] simple,powerful [101] powerful,easy [101] easy,practice [101] practice,amazing [101] amazing,healing [101] healing,diseases [98] #world_best_yoga,mystical Top Word Pairs in Tweet in G1:
[56] infected,blood [48] haemophilia,wales [43] lynne,kelly [42] children's,hospital [38] boarding,school [38] blood,inquiry [37] bruce,norval [34] kelly,haemophilia [34] haemophilia,centres [31] school,disabled Top Word Pairs in Tweet in G2:
[19] blood,transfusions [17] 25,million [17] million,blood [17] transfusions,carried [17] carried,eu [17] eu,year [17] year,million [17] million,litres [17] litres,blood [17] blood,plasma Top Word Pairs in Tweet in G3:
[25] bleeding,disorders [12] #haemophilia,article [10] converting,factor [10] single,metric [10] women,bleeding [10] gene,therapy [9] read,#haemophilia [9] article,converting [9] factor,nonfactor [9] nonfactor,usage Top Word Pairs in Tweet in G4:
[99] mystical,ancient [99] ancient,simple [99] simple,powerful [99] powerful,easy [99] easy,practice [99] practice,amazing [99] amazing,healing [99] healing,diseases [99] diseases,including [98] #world_best_yoga,mystical Top Word Pairs in Tweet in G5:
[17] last,weekend [16] acquired,hemophilia [16] lecture,gave [16] gave,last [16] weekend,canadian [16] canadian,hemophilia [16] hemophilia,clinicians [16] clinicians,#covid19 [16] #covid19,inherited [16] inherited,bleeding Top Word Pairs in Tweet in G6:
[72] #worldblooddonorday,blood [72] blood,needed [72] needed,regularly [72] regularly,patients [72] patients,diseases [72] diseases,such [72] such,thalassemia [72] thalassemia,haemophilia [71] mohfw_india,#worldblooddonorday Top Word Pairs in Tweet in G7:
[2] hankstern2,doubledoublejon [2] hugh_bothwell,godflythe [2] godflythe,adrianturner01 [2] pen_bird,macbareth [2] takethathistory,galcondude [2] suiwazear,malo_j [2] crispycurry,goatmunch [2] slsstudios,sicut_lupus [2] sicut_lupus,pg13scottwatson [2] pg13scottwatson,rayowen27617272 Top Word Pairs in Tweet in G9:
[46] midnight,sky [46] sky,jenlisa [46] jenlisa,wherein [46] wherein,alya [46] alya,girl [46] girl,hemophilia [46] hemophilia,unexpectedly [46] unexpectedly,meets [46] meets,stranger [46] stranger,anger Top Word Pairs in Tweet in G10:
[26] question,drug [26] drug,used [26] used,treatment [26] treatment,following [26] following,conditions [25] pharmafactz,question Top Replied-To in Entire Graph:
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Top Replied-To in G7:
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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:
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Top Mentioned in G9:
Top Mentioned in G10:
Top Tweeters in Entire Graph:
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Top Tweeters in G10: