The graph represents a network of 4,859 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, 21 April 2022 at 19:28 UTC.
The requested start date was Thursday, 21 April 2022 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 13-day, 23-hour, 47-minute period from Thursday, 07 April 2022 at 00:12 UTC to Thursday, 21 April 2022 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 : 4859
Unique Edges : 3281
Edges With Duplicates : 9665
Total Edges : 12946
Number of Edge Types : 5
Tweet : 2730
Retweet : 3709
MentionsInRetweet : 4520
Mentions : 1796
Replies to : 191
Self-Loops : 2934
Reciprocated Vertex Pair Ratio : 0.0362168874172185
Reciprocated Edge Ratio : 0.0699021370081885
Connected Components : 1151
Single-Vertex Connected Components : 699
Maximum Vertices in a Connected Component : 2197
Maximum Edges in a Connected Component : 8282
Maximum Geodesic Distance (Diameter) : 19
Average Geodesic Distance : 7.544833
Graph Density : 0.000212115879409051
Modularity : 0.408496
NodeXL Version : 1.0.1.449
Data Import : The graph represents a network of 4,859 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, 21 April 2022 at 19:28 UTC.
The requested start date was Thursday, 21 April 2022 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 13-day, 23-hour, 47-minute period from Thursday, 07 April 2022 at 00:12 UTC to Thursday, 21 April 2022 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:
[320] #womenshealth,#reproductivehealth [263] #reproductivehealth,#maternalmortality [206] enter,#win [188] life,expectancy [186] expectancy,women [184] uk,lower [184] oecd,average [183] women,england [183] #womenshealth,#womensfitness [183] average,life Top Word Pairs in Tweet in G1:
[59] need,#covidtest [45] ailsa30,#ad [45] #ad,need [45] #covidtest,#travel [44] #code,ailsa30 [40] #obgyn,#womenshealth [38] #discountcode,#code [36] #menshealth,#womenshealth [36] mira,fertility [35] #women,#womenshealth Top Word Pairs in Tweet in G2:
[182] life,expectancy [181] expectancy,women [180] average,life [178] women,england [178] england,uk [178] uk,lower [178] lower,global [178] global,oecd [178] oecd,average [178] average,particularly Top Word Pairs in Tweet in G3:
[32] funding,call [26] calling,researchers [26] researchers,funding [26] call,opened [26] opened,2022 [26] 2022,over [26] over,million [26] million,available [26] available,training [25] women,incredible Top Word Pairs in Tweet in G4:
[20] learn,more [19] black,women [18] dr,kathleen [18] kathleen,valenton [16] women,3x [16] 3x,more [16] more,die [16] die,pregnancy [16] pregnancy,related [16] related,cause Top Word Pairs in Tweet in G5:
[28] breast,cancer [17] #cervicalcancer,#hpv [16] #awareness,#womenshealth [15] #womenshealth,#breastcancer [15] cervical,cancer [15] #hpv,#awareness [12] #breastcancer,#women [12] learn,more [12] #papexamsavelives,#cervicalcancer [11] #breastcancer,#womenshealth Top Word Pairs in Tweet in G6:
[88] #womenshealth,#reproductivehealth [65] #reproductivehealth,#maternalmortality [46] african,american [46] american,mothers [46] mothers,dying [46] non,hispanic [46] hispanic,white [46] white,mothers [46] infants,born [44] pregnancy,childbirth Top Word Pairs in Tweet in G7:
[206] enter,#win [159] shoes,support [159] #win,pair [142] discoverself,need [141] check,enter [141] #win,best [128] proper,support [128] support,#feet [128] #feet,body [127] lagasse,shoes Top Word Pairs in Tweet in G8:
[154] underground,intelligence [97] #womenshealth,#menshealth [92] djmarcoandre,underground [77] intelligence,#muscle [77] #muscle,#fitness [77] #fitness,#magazine [76] intelligence,pinterest [76] pinterest,#pinterest [76] #pinterest,channels [58] #menshealth,#womenshealth Top Word Pairs in Tweet in G9:
[32] conversations,calvin [32] calvin,species [23] please,subscribe [22] #nutrition,#climatechange [20] women,health [20] interviews,global [20] #film,#singersongwriter [19] #singersongwriter,#nutrition [18] #hyivyhealth,#pelvicfloor [18] #aging,#womenshealth Top Word Pairs in Tweet in G10:
[181] #naturalskincare,#madeinusa [181] #madeinusa,#womensfashion [181] #womensfashion,#womensart [181] #womensart,#womenshealth [181] #womenshealth,#womensfitness [181] #womensfitness,#womensshoes [181] #womensshoes,#organicbeauty [181] #organicbeauty,#yoga [114] #yoga,#jewelry [114] #jewelry,#collagen Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G3:
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Top Replied-To in G6:
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Top Replied-To in G8:
Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
Top Mentioned in G2:
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Top Mentioned in G6:
Top Mentioned in G7:
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Top Mentioned in G9:
Top Mentioned in G10:
Top Tweeters in Entire Graph:
Top Tweeters in G1:
Top Tweeters in G2:
Top Tweeters in G3:
Top Tweeters in G4:
Top Tweeters in G5:
Top Tweeters in G6:
Top Tweeters in G7:
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Top Tweeters in G9:
Top Tweeters in G10: