The graph represents a network of 1,149 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, 26 January 2021 at 16:36 UTC.
The requested start date was Tuesday, 26 January 2021 at 01:01 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 10-day, 10-hour, 23-minute period from Tuesday, 12 January 2021 at 02:00 UTC to Friday, 22 January 2021 at 12:23 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 : 1149
Unique Edges : 947
Edges With Duplicates : 2017
Total Edges : 2964
Number of Edge Types : 5
Retweet : 710
MentionsInRetweet : 1103
Replies to : 186
Mentions : 479
Tweet : 486
Self-Loops : 491
Reciprocated Vertex Pair Ratio : 0.0404580152671756
Reciprocated Edge Ratio : 0.0777696258253852
Connected Components : 322
Single-Vertex Connected Components : 140
Maximum Vertices in a Connected Component : 421
Maximum Edges in a Connected Component : 2008
Maximum Geodesic Distance (Diameter) : 10
Average Geodesic Distance : 4.011955
Graph Density : 0.00103331786768073
Modularity : 0.429772
NodeXL Version : 1.0.1.443
Data Import : The graph represents a network of 1,149 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, 26 January 2021 at 16:36 UTC.
The requested start date was Tuesday, 26 January 2021 at 01:01 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 10-day, 10-hour, 23-minute period from Tuesday, 12 January 2021 at 02:00 UTC to Friday, 22 January 2021 at 12:23 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:
[93] willebrand,disease [63] haemophilia,centre [58] ash_hematology,isth [57] isth,nhf_hemophilia [56] clinical,practice [49] gene,therapy [43] manchester,haemophilia [42] disease,#vwd [41] bleeding,disorders [35] practice,guidelines Top Word Pairs in Tweet in G1:
[89] willebrand,disease [57] ash_hematology,isth [54] isth,nhf_hemophilia [53] clinical,practice [40] disease,#vwd [33] practice,guidelines [31] nhf_hemophilia,wfhemophilia [30] guidelines,willebrand [29] pleased,present [29] present,clinical Top Word Pairs in Tweet in G2:
[6] bleeding,disorders [6] gene,therapy [6] bleeding,disorder [6] hemophilia,혈우병 [5] #hemophilia,#vwd [5] therapies,treat [4] hemophilia,community [4] clotting,factor [4] bleed,bleed [4] please,join Top Word Pairs in Tweet in G3:
[61] haemophilia,centre [42] manchester,haemophilia [31] dr,bevan [31] haemosocuk_pi,dr [25] dr,david [25] david,bevan [25] infected,blood [25] blood,inquiry [24] dr,shirley [20] #contaminatedblood,#haemophilia Top Word Pairs in Tweet in G4:
[9] haemophilia,society [8] jaguar,enthusiasts [8] enthusiasts,club [8] club,raising [8] raising,funds [8] funds,support [8] support,vital [8] vital,work [8] work,conducted [8] conducted,haemophilia Top Word Pairs in Tweet in G5:
[4] 상대로,한 [2] 진짜,개지랄 [2] 개지랄,이렇게목소리가크신분들인거 [2] 이렇게목소리가크신분들인거,정말처음알앗음 [2] 정말처음알앗음,n번방때는 [2] n번방때는,너무침묵하셔서 [2] 너무침묵하셔서,도토리묵인줄알앗으니까 [2] 나,230억's [2] 230억's,girlfriend [2] 호그와트수님들중에는,젊었을적 Top Word Pairs in Tweet in G6:
[8] dr_philippaw,haemophilia [8] haemophilia,scandal [8] scandal,extended [8] extended,those [8] those,loved [8] loved,evidence [8] evidence,heard [8] heard,#bloodinquiry [8] #bloodinquiry,far [8] far,clearly Top Word Pairs in Tweet in G7:
[16] hemophilia,love [16] love,bleeding [16] bleeding,leenalblaihed [16] leenalblaihed,infuse [16] infuse,factor [16] factor,1st [16] 1st,investigate [16] investigate,later [16] later,treat [16] treat,bleeding Top Word Pairs in Tweet in G8:
[3] gene,therapy [3] #biomarin,tries [3] tries,#hemophilia [3] #hemophilia,#genetherapy [3] #genetherapy,back [3] back,track [3] track,positive [3] positive,data [3] diseases,#hemophilia [3] sgmo,#hemophilia Top Word Pairs in Tweet in G9:
[4] क,भ [3] ग,क [3] श,र [3] र,ण [3] म,ल [3] क,य [2] narendramodi,pmoindia [2] जनवर,2018 [2] 2018,क [2] भ,रत Top Word Pairs in Tweet in G10:
[12] bayer,development [12] development,portfolio [12] portfolio,cell [12] cell,gene [12] gene,therapies [12] therapies,already [12] already,comprises [12] comprises,advanced [12] advanced,assets [12] assets,different Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
Top Replied-To in G3:
Top Replied-To in G4:
Top Replied-To in G5:
Top Replied-To in G6:
Top Replied-To in G8:
Top Replied-To in G9:
Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
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: