The graph represents a network of 4,359 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 Friday, 15 November 2019 at 19:39 UTC.
The requested start date was Friday, 15 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 8-day, 0-hour, 57-minute period from Thursday, 07 November 2019 at 00:02 UTC to Friday, 15 November 2019 at 01:00 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 : 4359
Unique Edges : 4685
Edges With Duplicates : 2884
Total Edges : 7569
Number of Edge Types : 3
Tweet : 2044
Mentions : 5371
Replies to : 154
Self-Loops : 2044
Reciprocated Vertex Pair Ratio : 0.0383899488134016
Reciprocated Edge Ratio : 0.0739412950929868
Connected Components : 1078
Single-Vertex Connected Components : 624
Maximum Vertices in a Connected Component : 1477
Maximum Edges in a Connected Component : 3460
Maximum Geodesic Distance (Diameter) : 20
Average Geodesic Distance : 8.240172
Graph Density : 0.000234937742814185
Modularity : 0.618314
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 4,359 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 Friday, 15 November 2019 at 19:39 UTC.
The requested start date was Friday, 15 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 8-day, 0-hour, 57-minute period from Thursday, 07 November 2019 at 00:02 UTC to Friday, 15 November 2019 at 01:00 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 : Followers
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[254] please,retweet [253] everyone,please [245] yuck,parents [245] parents,imagine [239] retweet,bring [239] bring,woman [239] woman,justice [239] justice,yuck [238] africamustwake,everyone [238] imagine,treat Top Word Pairs in Tweet in G1:
[103] à,à [87] #womenshealth,#reproductivehealth [79] #reproductivehealth,#maternalmortality [46] #menshealth,#womenshealth [41] women's,health [40] link,bio [39] home,remedies [38] please,visit [38] visit,website [37] website,more Top Word Pairs in Tweet in G2:
[239] everyone,please [239] please,retweet [239] retweet,bring [239] bring,woman [239] woman,justice [239] justice,yuck [239] yuck,parents [239] parents,imagine [238] africamustwake,everyone [238] imagine,treat Top Word Pairs in Tweet in G3:
[37] great,advice [37] advice,tips [37] tips,maintain [37] maintain,vaginal [37] vaginal,health [37] health,drjengunter [37] drjengunter,#womenshealth [36] rcobsgyn,great [16] summary,study [12] dose,mode Top Word Pairs in Tweet in G4:
[29] co_rapunzel4,citizensfedup [29] citizensfedup,cherokeesher2 [28] cherokeesher2,mooncatadams [28] mooncatadams,agavecorn [25] agavecorn,gallaecian [14] realdonaldtrump,co_rapunzel4 [13] #fbi,#veterans [13] gallaecian,concit1usa [13] restlessnews,realdonaldtrump [12] #womenshealth,#fbi Top Word Pairs in Tweet in G5:
[176] #womenshealth,#ladieshealth [32] join,#wlgh19 [32] #wlgh19,discussion [32] discussion,excited [32] excited,kickoff [32] session,topic [24] plenary,session [23] fairness,research [23] research,minorities [23] wlgh19,join Top Word Pairs in Tweet in G6:
[16] women's,health [10] hello,anybody [10] anybody,hear [10] hear,read [10] read,one [10] one,thing [10] thing,today [10] today,please [10] please,read [10] read,important Top Word Pairs in Tweet in G7:
[23] women,s [14] female,mutilated [14] mutilated,male' [14] male',aristotle [14] aristotle,centuries [14] centuries,female [14] female,exclusion [14] exclusion,research [14] research,meant [14] meant,women Top Word Pairs in Tweet in G8:
[4] long,term [3] rihanna,shakira [2] womensmarch,womens_forum [2] womens_forum,womensmarchpar [2] femengermany,usa_femen [2] bruceandbrandon,brucelee [2] wearemums,afros_mums [2] afros_mums,drolesdemums [2] fpsychiatrie,ppupsy [2] shakira,madonna Top Word Pairs in Tweet in G9:
[16] take,care [10] #fluseason,here [10] here,tool [10] tool,help [10] help,find [10] find,closest [10] closest,place [10] place,flu [10] flu,shot [10] shot,gt Top Word Pairs in Tweet in G10:
[16] joebiden,guarantee [16] guarantee,protect [16] protect,family [16] family,mine [16] mine,joe [16] joe,biden [16] biden,#healthcare [16] #healthcare,#aca [16] #aca,#teambiden [15] hollesharon,joebiden Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G3:
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Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Tweeters in Entire Graph:
Top Tweeters in G1:
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Top Tweeters in G3:
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Top Tweeters in G5:
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Top Tweeters in G10: