The graph represents a network of 7,046 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 Monday, 11 October 2021 at 04:17 UTC.
The requested start date was Monday, 11 October 2021 at 00:01 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 5-day, 19-hour, 37-minute period from Sunday, 03 October 2021 at 09:23 UTC to Saturday, 09 October 2021 at 05:00 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 : 7046
Unique Edges : 4732
Edges With Duplicates : 11092
Total Edges : 15824
Number of Edge Types : 5
Retweet : 4949
MentionsInRetweet : 7019
Replies to : 150
Mentions : 1660
Tweet : 2046
Self-Loops : 2076
Reciprocated Vertex Pair Ratio : 0.0236931177134261
Reciprocated Edge Ratio : 0.0462894930198384
Connected Components : 1676
Single-Vertex Connected Components : 1254
Maximum Vertices in a Connected Component : 3169
Maximum Edges in a Connected Component : 9082
Maximum Geodesic Distance (Diameter) : 20
Average Geodesic Distance : 5.854399
Graph Density : 0.000164507513940128
Modularity : 0.52317
NodeXL Version : 1.0.1.447
Data Import : The graph represents a network of 7,046 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 Monday, 11 October 2021 at 04:17 UTC.
The requested start date was Monday, 11 October 2021 at 00:01 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 5-day, 19-hour, 37-minute period from Sunday, 03 October 2021 at 09:23 UTC to Saturday, 09 October 2021 at 05:00 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 : Betweenness Centrality
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[2038] armed,conflicts [2038] pregnant,woman [2035] fleeing,armed [2035] woman,lost [2035] lost,twins [2035] twins,due [2033] due,lack [2027] lack,medical [2024] medical,access [2021] conflicts,demoso Top Word Pairs in Tweet in G1:
[1060] maternal,care [1058] fleeing,armed [1058] armed,conflicts [1058] pregnant,woman [1058] woman,lost [1058] lost,twins [1058] twins,due [1058] due,lack [1058] lack,medical [1058] medical,access Top Word Pairs in Tweet in G2:
[560] maternal,health [339] maternal,mortality [288] #buildbackbetter,act [254] ranks,last [254] last,high [254] high,income [254] income,countries [254] countries,maternal [251] debates,#buildbackbetter [250] health,outcomes Top Word Pairs in Tweet in G3:
[863] fleeing,armed [863] armed,conflicts [863] pregnant,woman [863] woman,lost [863] lost,twins [863] twins,due [859] due,lack [857] conflicts,demoso [857] demoso,pregnant [855] lack,medical Top Word Pairs in Tweet in G4:
[290] momnibus,act [247] california,momnibus [202] nancyskinnerca,improve [199] #sb65,nancyskinnerca [189] act,#sb65 [182] improve,infant [159] governor,gavinnewsom [110] maternal,health [103] gavinnewsom,signs [91] live,governor Top Word Pairs in Tweet in G5:
[167] black,women [167] women,3x [167] 3x,more [167] more,white [167] white,women [167] women,die [167] die,issues [167] issues,related [167] related,pregnancy [167] pregnancy,learn Top Word Pairs in Tweet in G6:
[159] maternal,health [108] health,crisis [107] long,nation [107] nation,turned [107] turned,blind [107] blind,eye [107] eye,maternal [107] crisis,disproportionately [107] disproportionately,impacting [107] impacting,women Top Word Pairs in Tweet in G7:
[52] unfpa,woman [52] woman,dies [52] dies,related [52] related,causes [52] causes,many [52] many,more [52] more,suffer [52] suffer,disabilities [52] disabilities,ill [52] ill,health Top Word Pairs in Tweet in G8:
[150] build,better [150] better,plan [150] plan,proposed [150] proposed,today [150] take,look [150] look,medicaid [150] medicaid,expansion [150] expansion,cap [150] cap,child [150] child,care Top Word Pairs in Tweet in G9:
[49] #passthestork,share [49] share,hopes [47] continuing,celebration [47] celebration,10 [47] 10,year [47] year,anniversary [47] anniversary,asked [47] asked,everyone [47] everyone,#passthestork [46] msdformothers,continuing Top Word Pairs in Tweet in G10:
[78] looking,phd [78] phd,student [78] student,join [78] join,team [78] team,investigate [76] ozannelab,looking [74] investigate,metformin [74] metformin,during [74] during,pregnancy [74] pregnancy,impacts Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Replied-To in G6:
Top Replied-To in G7:
Top Replied-To in G9:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
Top Mentioned in G2:
Top Mentioned in G3:
Top Mentioned in G4:
Top Mentioned in G5:
Top Mentioned in G6:
Top Mentioned in G7:
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Top Mentioned in G10:
Top Tweeters in Entire Graph:
Top Tweeters in G1:
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Top Tweeters in G5:
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Top Tweeters in G9:
Top Tweeters in G10: