The graph represents a network of 5,096 Twitter users whose tweets in the requested range contained "#HPV", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Thursday, 11 July 2019 at 10:14 UTC.
The requested start date was Thursday, 11 July 2019 at 00:01 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 9-day, 11-hour, 5-minute period from Monday, 01 July 2019 at 00:37 UTC to Wednesday, 10 July 2019 at 11:42 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 : 5096
Unique Edges : 5701
Edges With Duplicates : 853
Total Edges : 6554
Number of Edge Types : 3
Tweet : 629
Mentions : 5838
Replies to : 87
Self-Loops : 629
Reciprocated Vertex Pair Ratio : 0.0129989015012816
Reciprocated Edge Ratio : 0.0256641966383517
Connected Components : 434
Single-Vertex Connected Components : 240
Maximum Vertices in a Connected Component : 4143
Maximum Edges in a Connected Component : 5461
Maximum Geodesic Distance (Diameter) : 21
Average Geodesic Distance : 4.0689
Graph Density : 0.000213101772754093
Modularity : 0.683044
NodeXL Version : 1.0.1.413
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[2827] cervical,cancer [2652] boys,aged [2609] died,cervical [2605] mother,died [2605] cancer,single [2605] single,mother [2605] mother,left [2605] left,behind [2605] behind,two [2605] two,boys Top Word Pairs in Tweet in G1:
[2587] mother,died [2587] died,cervical [2587] cervical,cancer [2587] cancer,single [2587] single,mother [2587] mother,left [2587] left,behind [2587] behind,two [2587] two,boys [2587] boys,aged Top Word Pairs in Tweet in G2:
[14] recommendations,â [14] â,updates [14] updates,#hpv [14] #hpv,vaccine [12] #acip,#vaccine [12] #vaccine,recommendations [12] #hpv,#hepa [12] #hepa,#menb [12] #menb,#flu [12] #flu,anti Top Word Pairs in Tweet in G3:
[61] ã,ã [42] #hpv,vaccine [39] ã,ム[37] ãƒ,ã [32] ãƒ,ム[21] hpv,vaccine [20] #hpv,#vaccine [19] ï,ï [18] ã,å [14] ì,ì Top Word Pairs in Tweet in G4:
[119] cervical,cancer [110] #hpv,vaccine [105] vaccine,exceeds [105] exceeds,expectations [105] expectations,raising [105] raising,hopes [105] hopes,cervical [105] cancer,eradicated [105] eradicated,#ccsm [101] medscape,#hpv Top Word Pairs in Tweet in G5:
[103] year,8 [99] vaccination,programme [96] boys,school [95] world,leading [95] leading,vaccination [95] programme,already [95] already,saved [95] saved,millions [95] millions,lives [95] lives,today Top Word Pairs in Tweet in G6:
[96] #cáncercervicouterino,prevenible [64] prevenible,#cáncercervicouterino [31] opsomsuruguay,#cáncercervicouterino [23] #hpv,vaccine [13] military,mom [13] mom,donna [13] donna,research [13] research,before [13] before,getting [13] getting,#hpvvaccine Top Word Pairs in Tweet in G7:
[21] #hpv,#vaccine [11] reducing,infections [10] #hpv,#vaccination [10] #hpv,vaccination [10] hpv,infection [10] cervical,cancer [9] analyse,sur [9] sur,60 [9] 60,millions [9] millions,personnes Top Word Pairs in Tweet in G8:
[32] #cdc,expanded [32] expanded,recommendations [32] recommendations,#hpv [31] #hpv,#vaccine [30] #vaccine,again [30] vaccine's,benefits [27] benefits,preventing [25] tarahaelle,#cdc [24] again,vaccine's [24] #mayoclinicminute,70 Top Word Pairs in Tweet in G9:
[23] #hpv,#vaccine [21] 12,13 [21] #hpv,vaccine [20] vaccine,boys [19] aged,12 [18] boys,aged [18] first,time [18] receive,#hpv [17] hpv,vaccine [17] welcome,phe_uk's Top Word Pairs in Tweet in G10:
[28] due,infections [26] 24,5 [26] 5,cancers [26] cancers,#africa [26] #africa,due [26] infections,comprehensive [26] comprehensive,study [24] study,issued [24] issued,international [24] international,collaboration Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Replied-To in G9:
Top Mentioned in Entire Graph:
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Top Mentioned in G10:
Top Tweeters in Entire Graph:
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Top Tweeters in G10: