The graph represents a network of 1,784 Twitter users whose tweets in the requested range contained "Preeclampsia", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Saturday, 09 November 2019 at 20:15 UTC.
The requested start date was Wednesday, 06 November 2019 at 01:01 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, 40-minute period from Wednesday, 23 October 2019 at 01:13 UTC to Wednesday, 06 November 2019 at 00:54 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 : 1784
Unique Edges : 1784
Edges With Duplicates : 335
Total Edges : 2119
Number of Edge Types : 3
Tweet : 428
Mentions : 1438
Replies to : 253
Self-Loops : 428
Reciprocated Vertex Pair Ratio : 0.0285714285714286
Reciprocated Edge Ratio : 0.0555555555555556
Connected Components : 465
Single-Vertex Connected Components : 229
Maximum Vertices in a Connected Component : 227
Maximum Edges in a Connected Component : 331
Maximum Geodesic Distance (Diameter) : 10
Average Geodesic Distance : 3.213793
Graph Density : 0.000497976655458
Modularity : 0.779632
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 1,784 Twitter users whose tweets in the requested range contained "Preeclampsia", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Saturday, 09 November 2019 at 20:15 UTC.
The requested start date was Wednesday, 06 November 2019 at 01:01 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, 40-minute period from Wednesday, 23 October 2019 at 01:13 UTC to Wednesday, 06 November 2019 at 00:54 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".
Layout Algorithm : The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.
Graph Source : GraphServerTwitterSearch
Graph Term : Preeclampsia
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 : Followers
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[225] gave,birth [219] life,threatening [218] preeclampsia,gave [217] one,migrant [217] migrant,mother [217] mother,denied [217] denied,medication [217] medication,life [217] threatening,preeclampsia [217] birth,prematurely Top Word Pairs in Tweet in G1:
[21] 76,000 [16] blood,pressure [15] pregnant,women [15] way,predict [14] researchers,developed [14] kills,76 [13] each,year [12] predict,onset [12] onset,deadly [12] deadly,pregnancy Top Word Pairs in Tweet in G2:
[212] one,migrant [212] migrant,mother [212] mother,denied [212] denied,medication [212] medication,life [212] life,threatening [212] threatening,preeclampsia [212] preeclampsia,gave [212] gave,birth [212] birth,prematurely Top Word Pairs in Tweet in G3:
[13] low,dose [13] prevent,delay [13] delay,onset [9] patients,know [9] know,#aspirin [9] #aspirin,low [9] dose,aspirin [9] aspirin,recommended [9] recommended,acog [9] acog,prevent Top Word Pairs in Tweet in G4:
[36] maternal,mortality [32] postpartum,hemorrhage [31] fix,targets [28] hospital,safety [28] safety,fix [28] rate,postpartum [28] hemorrhage,preeclampsia [27] targets,maternal [27] mortality,rate [22] preeclampsia,usatoday Top Word Pairs in Tweet in G5:
[63] preeclampsia,chingaderas [62] orlandorpn,preeclampsia Top Word Pairs in Tweet in G6:
[47] luego,9 [47] 9,abortos [47] hija,nacio [47] nacio,32 [47] 32,semanas [47] semanas,embarazada [47] oligohidramnios,placenta [47] placenta,acreta [46] julietasagnay,luego [40] abortos,espontã Top Word Pairs in Tweet in G8:
[21] first,time [20] being,pregnant [20] pregnant,first [20] time,homestretch [20] homestretch,wild [20] wild,contraction [20] contraction,cramp [20] cramp,heel [20] heel,popping [20] popping,through Top Word Pairs in Tweet in G9:
[13] cause,maternal [13] maternal,death [12] #preeclampsia,second [12] second,common [12] common,cause [12] death,accounts [12] accounts,around [12] around,20 [12] 20,stillbirths [12] stillbirths,up Top Word Pairs in Tweet in G10:
[2] gestational,diabetes [2] omarhamada,yudiferdi1 [2] yudiferdi1,really [2] really,preeclampsia [2] preeclampsia,problem [2] problem,fatal [2] fatal,complications [2] complications,big [2] big,deal [2] deal,ob Top Replied-To in Entire Graph:
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Top Mentioned in Entire Graph:
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Top Tweeters in Entire Graph:
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Top Tweeters in G10: