The graph represents a network of 4,990 Twitter users whose tweets in the requested range contained "Maternal health", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Thursday, 21 November 2019 at 20:54 UTC.
The requested start date was Tuesday, 19 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 5-day, 23-hour, 13-minute period from Wednesday, 13 November 2019 at 01:45 UTC to Tuesday, 19 November 2019 at 00:59 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 : 4990
Unique Edges : 6583
Edges With Duplicates : 1267
Total Edges : 7850
Number of Edge Types : 3
Tweet : 760
Mentions : 6878
Replies to : 212
Self-Loops : 760
Reciprocated Vertex Pair Ratio : 0.0287873914441943
Reciprocated Edge Ratio : 0.0559637329998437
Connected Components : 646
Single-Vertex Connected Components : 290
Maximum Vertices in a Connected Component : 3054
Maximum Edges in a Connected Component : 5651
Maximum Geodesic Distance (Diameter) : 19
Average Geodesic Distance : 7.391008
Graph Density : 0.000256958093376571
Modularity : 0.783975
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 4,990 Twitter users whose tweets in the requested range contained "Maternal health", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Thursday, 21 November 2019 at 20:54 UTC.
The requested start date was Tuesday, 19 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 5-day, 23-hour, 13-minute period from Wednesday, 13 November 2019 at 01:45 UTC to Tuesday, 19 November 2019 at 00:59 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 : Maternal health
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:
[1399] maternal,health [702] maternal,mortality [295] infant,maternal [292] maternal,child [279] black,women [273] child,health [261] #1,medical [261] medical,bankruptcies [261] bankruptcies,#1 [261] #1,rural Top Word Pairs in Tweet in G1:
[251] maternal,health [85] maternal,mortality [64] health,subcommittee [59] black,women [50] improve,maternal [43] women,america [43] america,face [43] face,maternal [43] mortality,crisis [43] crisis,s Top Word Pairs in Tweet in G2:
[98] maternal,health [61] first,lady [48] maternal,newborn [43] child,health [40] maternal,child [28] new,zealand [28] privileged,serve [28] serve,country [28] country,shown [28] shown,leadership Top Word Pairs in Tweet in G3:
[116] maternal,health [47] child,health [44] maternal,child [30] health,care [29] u,s [26] maternal,mortality [24] s,maternal [22] medicaid,tweak [21] mental,health [21] tweak,offer Top Word Pairs in Tweet in G4:
[257] #1,medical [257] medical,bankruptcies [257] bankruptcies,#1 [257] #1,rural [257] rural,hospital [257] hospital,closures [257] closures,#1 [257] #1,min [257] min,wage [257] wage,jobs Top Word Pairs in Tweet in G5:
[188] black,woman [183] harris,2020 [183] 2020,democratic [183] democratic,primary [183] primary,s [183] s,lone [183] lone,black [183] woman,hold [183] hold,columbia [183] columbia,town Top Word Pairs in Tweet in G6:
[70] maternal,deaths [66] gender,based [51] maternal,health [51] #icpd25,comes [51] comes,end [51] end,thank [51] thank,governments [51] governments,#kenya [51] #kenya,#denmark [51] #denmark,partner Top Word Pairs in Tweet in G7:
[101] maternal,mortality [96] black,women [51] women,3 [42] maternal,infant [42] infant,health [36] health,crisis [34] abortion,restrictions [30] pregnancy,related [29] mortality,abortion [29] more,pregnancy Top Word Pairs in Tweet in G8:
[111] better,tools [111] tools,collecting [111] collecting,sharing [111] sharing,data [111] data,help [111] help,community [111] community,health [111] health,workers [111] workers,protect [111] protect,families Top Word Pairs in Tweet in G9:
[34] maternal,health [19] maternal,mortality [14] around,world [14] health,care [13] improve,health [11] women,deserve [11] deserve,healthy [11] healthy,pregnancy [11] pregnancy,safe [11] safe,childbirth Top Word Pairs in Tweet in G10:
[265] maternal,health [83] improve,maternal [51] masaka,run [51] run,improve [48] good,morning [47] improving,maternal [47] mtnug,good [44] running,maternal [43] mtn,masaka [43] health,#mtnmarathon 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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