The graph represents a network of 1,790 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 Friday, 08 November 2019 at 20:14 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 : 1790
Unique Edges : 1791
Edges With Duplicates : 333
Total Edges : 2124
Number of Edge Types : 3
Tweet : 428
Mentions : 1442
Replies to : 254
Self-Loops : 428
Reciprocated Vertex Pair Ratio : 0.0291450777202073
Reciprocated Edge Ratio : 0.0566393958464443
Connected Components : 467
Single-Vertex Connected Components : 230
Maximum Vertices in a Connected Component : 227
Maximum Edges in a Connected Component : 332
Maximum Geodesic Distance (Diameter) : 10
Average Geodesic Distance : 3.218549
Graph Density : 0.000496204302519119
Modularity : 0.779888
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 1,790 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 Friday, 08 November 2019 at 20:14 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 [17] 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:
[37] 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] abortos,espontáneos [47] espontáneos,hija [47] hija,nacio [47] nacio,32 [47] 32,semanas [47] semanas,embarazada [47] embarazada,añosa [47] añosa,oligohidramnios 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:
[34] lost,memory [34] memory,during [34] during,childbirth [29] husband,writes [29] writes,book [29] book,wife [29] wife,lost [27] independent,husband [5] woman,lost [5] childbirth,husband 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: