The graph represents a network of 1,644 Twitter users whose recent tweets were included in a list (Tweet ID List - @gmcuk) of 3200 tweet IDs, or who were replied to or mentioned in those tweets. 3200 out of 3200 tweets were collected. The network was obtained from Twitter on Wednesday, 08 July 2020 at 17:01 UTC.
The tweets in the network were tweeted over the 779-day, 6-hour, 10-minute period from Friday, 18 May 2018 at 09:50 UTC to Sunday, 05 July 2020 at 16:01 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 : 1644
Unique Edges : 2453
Edges With Duplicates : 6925
Total Edges : 9378
Self-Loops : 904
Reciprocated Vertex Pair Ratio : 0.156762295081967
Reciprocated Edge Ratio : 0.271036315323295
Connected Components : 1
Single-Vertex Connected Components : 0
Maximum Vertices in a Connected Component : 1644
Maximum Edges in a Connected Component : 9378
Maximum Geodesic Distance (Diameter) : 2
Average Geodesic Distance : 1.996617
Graph Density : 0.0012539372964712
Modularity : 0.196034
NodeXL Version : 1.0.1.437
Data Import : The graph represents a network of 1,644 Twitter users whose recent tweets were included in a list (Tweet ID List - @gmcuk) of 3200 tweet IDs, or who were replied to or mentioned in those tweets. 3200 out of 3200 tweets were collected. The network was obtained from Twitter on Wednesday, 08 July 2020 at 17:01 UTC.
The tweets in the network were tweeted over the 779-day, 6-hour, 10-minute period from Friday, 18 May 2018 at 09:50 UTC to Sunday, 05 July 2020 at 16:01 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 : TwitterIDList
Graph Term : Tweet ID List - @gmcuk
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
Vertex Alpha : Followers
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[237] clare,marx [224] dame,clare [190] find,out [132] uk,practice [130] medical,students [130] out,more [125] welcome,uk [114] looking,forward [83] patient,safety [79] gmc,uk Top Word Pairs in Tweet in G1:
[166] clare,marx [165] dame,clare [157] find,out [106] out,more [97] uk,practice [93] welcome,uk [93] medical,students [73] gmc,uk [70] uk,org [65] looking,forward Top Word Pairs in Tweet in G2:
[43] clare,marx [36] looking,forward [32] dame,clare [28] 12,00 [27] gmcuk,nhs_healthedeng [25] welcome,uk [25] uk,practice [25] find,out [24] nhs_healthedeng,rcgp [24] rcgp,thebma Top Word Pairs in Tweet in G3:
[6] dame,clare [6] clare,marx [5] gmcuk,ni [5] ni,team [3] gmcuk,chair [3] chair,dame [3] gmcuk,education [3] forward,working [2] gmcuk,_nimdta [2] special,thanks Top Word Pairs in Tweet in G4:
[7] medical,students [5] welcomed,valued [4] new,uk [3] students,doctors [3] reflective,practice [3] don,t [3] looking,forward [3] #ablemedics,#doctorswithdisabilities [3] student,professionalism [3] #gmcconf,today Top Word Pairs in Tweet in G5:
[3] wellbeing,doctors [2] report,wellbeing [2] full,response [2] first,survey [2] survey,sas [2] sas,doctors [2] t,done [2] support,career [2] published,today [2] state,medical Top Word Pairs in Tweet in G6:
[4] general,medical [4] medical,council [3] medical,students [3] patient,feedback [3] gt,gt [2] sas,doctors [2] welcome,gmcuk [2] gmcuk,report [2] learning,outcomes [2] generic,professional Top Word Pairs in Tweet in G7:
[2] thebma,bapiouk [2] bapiouk,bidauk [2] bapiouk,bapionortheast [2] bapionortheast,jsbamrah [2] welcome,uk [2] uk,practice Top Word Pairs in Tweet in G8:
[3] staff,network [2] panel,diversity [2] diversity,discrimination [2] looking,forward [2] proud,work Top Word Pairs in Tweet in G9:
[6] physician,associates [4] sign,up [4] read,full [3] full,statement [2] nhs,workforce [2] don,t [2] birthday,nhs [2] mental,health [2] full,response [2] sas,locally Top Word Pairs in Tweet in G10:
[2] spread,word [2] really,important [2] great,work Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
Top Replied-To in G3:
Top Replied-To in G4:
Top Replied-To in G5:
Top Replied-To in G8:
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:
Top Mentioned in G4:
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: