The graph represents a network of 2,572 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, 12 May 2020 at 16:39 UTC.
The requested start date was Tuesday, 12 May 2020 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, 22-hour, 17-minute period from Tuesday, 28 April 2020 at 01:12 UTC to Monday, 11 May 2020 at 23:30 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 : 2572
Unique Edges : 1501
Edges With Duplicates : 4604
Total Edges : 6105
Number of Edge Types : 5
Retweet : 1789
MentionsInRetweet : 2330
Mentions : 1066
Replies to : 243
Tweet : 677
Self-Loops : 693
Reciprocated Vertex Pair Ratio : 0.0235057085292142
Reciprocated Edge Ratio : 0.0459317585301837
Connected Components : 412
Single-Vertex Connected Components : 192
Maximum Vertices in a Connected Component : 697
Maximum Edges in a Connected Component : 2192
Maximum Geodesic Distance (Diameter) : 16
Average Geodesic Distance : 3.224076
Graph Density : 0.000460937372402917
Modularity : 0.480978
NodeXL Version : 1.0.1.432
Data Import : The graph represents a network of 2,572 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, 12 May 2020 at 16:39 UTC.
The requested start date was Tuesday, 12 May 2020 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, 22-hour, 17-minute period from Tuesday, 28 April 2020 at 01:12 UTC to Monday, 11 May 2020 at 23:30 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:
[733] credible,domestic [733] domestic,foreign [733] foreign,intelligence [733] intelligence,determined [733] determined,beyond [715] 10,credible [715] beyond,dispute [715] dispute,buhari [712] mazinnamdikanu,10 [705] buhari,died Top Word Pairs in Tweet in G1:
[731] credible,domestic [731] domestic,foreign [731] foreign,intelligence [731] intelligence,determined [731] determined,beyond [713] 10,credible [713] beyond,dispute [713] dispute,buhari [712] mazinnamdikanu,10 [703] buhari,died Top Word Pairs in Tweet in G2:
[72] one,year [72] year,ago [44] ago,today [41] collins_law,one [39] blood,scandal [38] contaminated,blood [31] make,sure [30] sure,copy [28] covid,19 [27] infected,blood Top Word Pairs in Tweet in G3:
[36] hemophilia,causes [36] causes,symptoms [36] symptoms,diagnosis [34] ë,ì [27] ãƒ,ム[25] ì,ì [24] ì,ë [19] article,hemophilia [19] ì,í [19] diagnosis,treatment Top Word Pairs in Tweet in G4:
[133] midnight,sky [133] sky,jenlisa [133] jenlisa,wherein [133] wherein,alya [133] alya,girl [133] girl,hemophilia [133] hemophilia,unexpectedly [133] unexpectedly,meets [133] meets,stranger [133] stranger,anger Top Word Pairs in Tweet in G5:
[26] bleeding,disorders [20] covid,19 [18] hemophilia,phase [12] disorders,community [12] #hemophilia,#vwd [11] tireless,together [11] together,fund [10] 50,donations [10] breaking,news [10] news,pfe Top Word Pairs in Tweet in G6:
[32] य,ज [22] free,blood [22] blood,transfusions [22] transfusions,blood [22] blood,collection [22] collection,transportation [22] transportation,vans [22] vans,integrated [22] integrated,care [22] care,centres Top Word Pairs in Tweet in G7:
[6] coachforpotus,charliedonahue4 [6] charliedonahue4,sparknottle [6] sparknottle,logicalinstaffs [6] logicalinstaffs,alex1100today [6] alex1100today,deepblue910 [6] deepblue910,sandcrapper [6] shawngrams,daveycrokett [6] daveycrokett,spooney35 [6] spooney35,magarosco [6] magarosco,cigarvolante Top Word Pairs in Tweet in G10:
[33] fanbytemedia,wrote [33] wrote,aids [33] aids,hemophilia [33] hemophilia,covid [33] covid,pathologic [33] pain,frames [33] frames,pain [32] violetfyi,fanbytemedia [32] pathologic,œitâ [32] œitâ,pain Top Replied-To in Entire Graph:
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Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Tweeters in Entire Graph:
Top Tweeters in G1:
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Top Tweeters in G10: