The graph represents a network of 6,114 Twitter users whose tweets in the requested range contained "womenshealth", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Thursday, 29 October 2020 at 19:31 UTC.
The requested start date was Thursday, 29 October 2020 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 11-day, 10-hour, 7-minute period from Saturday, 17 October 2020 at 13:53 UTC to Thursday, 29 October 2020 at 00:00 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 : 6114
Unique Edges : 6968
Edges With Duplicates : 12175
Total Edges : 19143
Number of Edge Types : 5
Tweet : 2712
Retweet : 4047
MentionsInRetweet : 8659
Replies to : 199
Mentions : 3526
Self-Loops : 2843
Reciprocated Vertex Pair Ratio : 0.0259127150650441
Reciprocated Edge Ratio : 0.0505164127211371
Connected Components : 1319
Single-Vertex Connected Components : 828
Maximum Vertices in a Connected Component : 3264
Maximum Edges in a Connected Component : 13854
Maximum Geodesic Distance (Diameter) : 17
Average Geodesic Distance : 6.651604
Graph Density : 0.000261646311017116
Modularity : 0.483731
NodeXL Version : 1.0.1.441
Data Import : The graph represents a network of 6,114 Twitter users whose tweets in the requested range contained "womenshealth", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Thursday, 29 October 2020 at 19:31 UTC.
The requested start date was Thursday, 29 October 2020 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 11-day, 10-hour, 7-minute period from Saturday, 17 October 2020 at 13:53 UTC to Thursday, 29 October 2020 at 00:00 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 : womenshealth
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:
[546] menopause,day [544] world,menopause [529] know,re [512] re,going [512] day,today [510] today,pretend [510] pretend,know [510] going,try [510] try,show [510] show,care Top Word Pairs in Tweet in G1:
[179] #womenshealth,#reproductivehealth [161] #reproductivehealth,#maternalmortality [67] breast,cancer [54] learn,more [47] #menshealth,#womenshealth [38] african,american [37] pregnancy,childbirth [37] women,die [36] infants,born [36] american,mothers Top Word Pairs in Tweet in G2:
[259] achy,joints [258] hot,flushes [258] mood,swings [257] flushes,night [257] night,sweats [257] sweats,palpitations [257] palpitations,anxiety [257] anxiety,mood [257] swings,achy [257] joints,fatigue Top Word Pairs in Tweet in G3:
[506] world,menopause [506] menopause,day [504] day,today [504] today,pretend [504] pretend,know [504] know,re [504] re,going [504] going,try [504] try,show [504] show,care Top Word Pairs in Tweet in G4:
[279] womenshealth,asnadvocacy [279] kidneynews,jasn_news [279] jasn_news,cjasn [279] cjasn,asnkidney360 [278] mwlorg_en,womenshealth [278] asnadvocacy,kidneynews [278] asnkidney360,asncommunities [277] asncommunities,asnkidney [277] asnkidney,jack [276] ahmed_lateefah,mwlorg_en Top Word Pairs in Tweet in G5:
[16] #femtech,#womenshealth [15] #womenshealth,#wellness [15] #femtech,#femtechfocus [15] #femtechfocus,#womenshealth [14] beanstalks,giant [14] international,competition [14] competition,prizes [14] prizes,#healthcare [14] #healthcare,tech [14] tech,#startups Top Word Pairs in Tweet in G6:
[34] co_rapunzel4,citizensfedup [31] #latino,#latinos [30] doris03763159,network_gal [30] #womenshealth,#fbi [29] restlessnews,pattikimble [29] #fbi,#veterans [27] network_gal,gualcojodie [27] gualcojodie,itridpm [27] wufi_desade,nic6454 [27] network_gal,doris03763159 Top Word Pairs in Tweet in G7:
[17] next,#figowebinar [17] 3pm,gmt [17] gmt,exploring [17] exploring,innovations [17] innovations,become [17] become,best [17] best,practices [15] join,next [15] #figowebinar,29th [15] 29th,october Top Word Pairs in Tweet in G8:
[13] looking,forward [11] #menopause,#workplace [11] #workplace,dianedanz [11] dianedanz,tzeng_sophia [11] tzeng_sophia,rowan_rachel [11] #menopause,#womenshealth [8] talk,#menopause [8] dr,wen [8] wen,shen [8] drmarla,dr Top Word Pairs in Tweet in G9:
[54] find,facts [54] facts,wearing [54] wearing,narrow [54] narrow,shoes [54] shoes,surprised [54] surprised,#womenshealth [54] #womenshealth,#shoes [54] #shoes,#lugz [54] #lugz,#narrowshoes [54] #narrowshoes,#foothealth Top Word Pairs in Tweet in G10:
[12] letysha,montgomery [9] ugroundbreakers,check [8] featured,artist [8] artist,week [8] week,letysha [7] check,#blog [6] lactation,consultant [6] consultant,rn [6] thank,mededportal [6] mededportal,featuring 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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