The graph represents a network of 531 Twitter users whose recent tweets contained "#Skincancer", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 18,000 tweets. The network was obtained from Twitter on Friday, 11 June 2021 at 00:06 UTC.
The tweets in the network were tweeted over the 8-day, 2-hour, 6-minute period from Wednesday, 02 June 2021 at 21:54 UTC to Friday, 11 June 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 : 531
Unique Edges : 554
Edges With Duplicates : 184
Total Edges : 738
Number of Edge Types : 5
Mentions : 140
Tweet : 212
Retweet : 244
MentionsInRetweet : 133
Replies to : 9
Self-Loops : 217
Reciprocated Vertex Pair Ratio : 0.0240700218818381
Reciprocated Edge Ratio : 0.047008547008547
Connected Components : 189
Single-Vertex Connected Components : 105
Maximum Vertices in a Connected Component : 45
Maximum Edges in a Connected Component : 102
Maximum Geodesic Distance (Diameter) : 11
Average Geodesic Distance : 2.809345
Graph Density : 0.00166293572113847
Modularity : 0.705863
NodeXL Version : 1.0.1.445
Data Import : The graph represents a network of 531 Twitter users whose recent tweets contained "#Skincancer", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 18,000 tweets. The network was obtained from Twitter on Friday, 11 June 2021 at 00:06 UTC.
The tweets in the network were tweeted over the 8-day, 2-hour, 6-minute period from Wednesday, 02 June 2021 at 21:54 UTC to Friday, 11 June 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 : TwitterSearch
Graph Term : #Skincancer
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:
[105] skin,cancer [22] #skincancer,#albinsm [21] #skincancer,#melanoma [21] body,skin [21] skin,exam [20] biopsy,results [20] results,back [20] back,moles [20] moles,cancerous [20] cancerous,hooray Top Word Pairs in Tweet in G1:
[31] skin,cancer [10] health,symptoms [7] see,doctor [5] sun,cream [5] #skincancer,#sunsafety [5] insatiable,thirst [5] thirst,loss [5] loss,appetite [5] appetite,unexpected [5] unexpected,weight Top Word Pairs in Tweet in G2:
[20] biopsy,results [20] results,back [20] back,moles [20] moles,cancerous [20] cancerous,hooray [20] hooray,update [20] update,#skincancer [20] #skincancer,blog [20] blog,whole [20] whole,saga Top Word Pairs in Tweet in G3:
[4] #lungcancer,#skincancer [2] thank,everyone [2] everyone,joined [2] joined,live [2] live,last [2] last,#webinar [2] #webinar,#oncology [2] #oncology,update [2] update,part [2] part,lung Top Word Pairs in Tweet in G4:
[22] #skincancer,#albinsm [17] damasse,story [17] story,part [16] albicare,cameroon [16] cameroon,vopaca [13] ces,prochains [13] prochains,jours [13] jours,ferons [13] ferons,focus [13] focus,jeune Top Word Pairs in Tweet in G5:
[12] bcc,within [11] #melanomaawareness,#skincancer [9] skin,cancer [9] basal,cell [9] cell,carcinoma [6] having,basal [6] carcinoma,puts [6] puts,risk [6] risk,developing [6] developing,more Top Word Pairs in Tweet in G6:
[13] melanoma,pathology [13] pathology,approaches [13] approaches,classification [13] classification,brjdermatol [13] brjdermatol,#dermatology [13] #dermatology,#skincancer [13] #skincancer,#dermatologia [13] #dermatologia,#cancerdepiel Top Word Pairs in Tweet in G7:
[10] skin,cancer [6] asco,oncoalert [6] oncoalert,#skincancer [5] feeling,better [5] better,extra [5] extra,cup [5] cup,morning [5] morning,caffeine [5] caffeine,prevents [5] prevents,skin Top Word Pairs in Tweet in G8:
[8] know,someone [8] someone,loves [8] loves,sunbathe [8] sunbathe,spent [8] spent,time [8] time,tanning [8] tanning,beds [8] beds,share [8] share,skin [8] skin,check Top Word Pairs in Tweet in G9:
[12] outdoor,workers [12] workers,including [12] including,those [12] those,#construction [12] #construction,agriculture [12] agriculture,landscaping [12] landscaping,risk [12] risk,sunburn [12] sunburn,#skincancer [12] #skincancer,train Top Word Pairs in Tweet in G10:
[7] #btsm,#braintumor [7] #cancer,#breastcancer [7] #breastcancer,#lungcancer [7] #lungcancer,#skincancer [5] thanks,generous [5] generous,sponsors [5] sponsors,offer [5] offer,free [5] free,education [5] education,resources Top Replied-To in Entire Graph:
Top Replied-To in G6:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
Top Mentioned in G3:
Top Mentioned in G5:
Top Mentioned in G6:
Top Mentioned in G7:
Top Mentioned in G8:
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:
Top Tweeters in G8:
Top Tweeters in G9:
Top Tweeters in G10: