The graph represents a network of 4,704 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, 07 October 2021 at 19:30 UTC.
The requested start date was Thursday, 07 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 10-day, 13-hour, 54-minute period from Sunday, 26 September 2021 at 10:06 UTC to Thursday, 07 October 2021 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 : 4704
Unique Edges : 3497
Edges With Duplicates : 9612
Total Edges : 13109
Number of Edge Types : 5
Tweet : 3341
Retweet : 3512
MentionsInRetweet : 4052
Mentions : 2021
Replies to : 183
Self-Loops : 4073
Reciprocated Vertex Pair Ratio : 0.0437392795883362
Reciprocated Edge Ratio : 0.0838126540673788
Connected Components : 1305
Single-Vertex Connected Components : 812
Maximum Vertices in a Connected Component : 1954
Maximum Edges in a Connected Component : 6471
Maximum Geodesic Distance (Diameter) : 24
Average Geodesic Distance : 9.228866
Graph Density : 0.000220043364996434
Modularity : 0.397357
NodeXL Version : 1.0.1.447
Data Import : The graph represents a network of 4,704 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, 07 October 2021 at 19:30 UTC.
The requested start date was Thursday, 07 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 10-day, 13-hour, 54-minute period from Sunday, 26 September 2021 at 10:06 UTC to Thursday, 07 October 2021 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:
[1588] #womenshealth,#womensfitness [1574] #womensart,#womenshealth [1572] #naturalskincare,#madeinusa [1572] #madeinusa,#womensfashion [1572] #womensfashion,#womensart [1572] #womensfitness,#womensshoes [1572] #womensshoes,#organicbeauty [1572] #organicbeauty,#yoga [815] #yoga,#jewelry [815] #jewelry,#collagen Top Word Pairs in Tweet in G1:
[80] breast,cancer [78] health,fitness [78] fitness,day [67] women's,health [60] women,health [45] learn,more [43] #menshealth,#womenshealth [38] national,women's [33] awareness,month [30] national,women Top Word Pairs in Tweet in G2:
[47] blood,pressure [46] mental,health [36] question,related [36] related,someone's [36] someone's,mental [36] health,solve [36] solve,queries [36] queries,questions [36] questions,during [35] lalitku60798629,question Top Word Pairs in Tweet in G3:
[239] #womenshealth,#reproductivehealth [206] #reproductivehealth,#maternalmortality [71] pregnancy,childbirth [70] women,die [70] maternal,death [70] death,rate [70] african,american [70] american,mothers [70] mothers,dying [70] non,hispanic Top Word Pairs in Tweet in G4:
[27] #femtech,#womenshealth [19] #womenshealth,#femtech [16] market,map [14] map,#womenshealth [14] #femtech,startups [14] startups,rock_health [14] rock_health,exciting [14] exciting,update [13] healthythinker,market [11] #menstruation,#menopause Top Word Pairs in Tweet in G5:
[50] hormone,therapy [50] increased,#dementia [50] #dementia,risk [27] study,hormone [27] therapy,associated [27] associated,increased [27] risk,#alzheimers [26] lead_coalition,study [24] #alzheimers,#womenshealth [23] menopausal,hormone Top Word Pairs in Tweet in G6:
[24] ai,health [23] #primaryhealthcare,#generalpractice [22] women,health [20] women,lead [20] lead,longer [20] longer,healthier [20] healthier,lives [20] lives,first [20] first,global [20] global,index Top Word Pairs in Tweet in G7:
[36] women,health [35] pre,recorded [25] recorded,lectures [23] #menopause,#womenshealth [22] health,professionals [20] watch,pre [19] womenâ,health [16] health,meeting [14] registration,open [14] open,health Top Word Pairs in Tweet in G8:
[43] bringing,home [43] home,#breastcancerawareness [43] #breastcancerawareness,month [43] month,quality [43] quality,products [40] healthy,begins [40] begins,feet [40] feet,bringing [40] products,support [39] discoverself,healthy Top Word Pairs in Tweet in G9:
[4] woman,21 [4] 21,pap [4] pap,smear [4] smear,regularly [4] regularly,ppfa [4] ppfa,gives [4] gives,great [4] great,info [4] info,regarding [4] regarding,pap Top Word Pairs in Tweet in G10:
[46] #womensfitness,#fitness [43] #fitness,#fitnessmotivation [39] #women,#girls [39] #womenintech,#womeninstem [39] #fitnessmotivation,#womenshealth [29] #womenshealth,#workout [24] #workout,#gym [24] #gym,#fitgirl [24] #fitgirl,#femalemuscle [24] #femalemuscle,#girlswithmuscles Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
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Top Replied-To in G6:
Top Replied-To in G7:
Top Replied-To in G9:
Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
Top Mentioned in G2:
Top Mentioned in G3:
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Top Mentioned in G5:
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:
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Top Tweeters in G7:
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Top Tweeters in G9:
Top Tweeters in G10: