The graph represents a network of 1,294 Twitter users whose recent tweets were included in a list (Tweet ID List - thebma) 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 Tuesday, 07 July 2020 at 21:55 UTC.
The tweets in the network were tweeted over the 727-day, 5-hour, 51-minute period from Wednesday, 11 July 2018 at 12:58 UTC to Tuesday, 07 July 2020 at 18:50 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 : 1294
Unique Edges : 1964
Edges With Duplicates : 5483
Total Edges : 7447
Self-Loops : 1157
Reciprocated Vertex Pair Ratio : 0.122829861111111
Reciprocated Edge Ratio : 0.218786238886741
Connected Components : 1
Single-Vertex Connected Components : 0
Maximum Vertices in a Connected Component : 1294
Maximum Edges in a Connected Component : 7447
Maximum Geodesic Distance (Diameter) : 2
Average Geodesic Distance : 1.995702
Graph Density : 0.00154619273199764
Modularity : 0.184534
NodeXL Version : 1.0.1.437
Data Import : The graph represents a network of 1,294 Twitter users whose recent tweets were included in a list (Tweet ID List - thebma) 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 Tuesday, 07 July 2020 at 21:55 UTC.
The tweets in the network were tweeted over the 727-day, 5-hour, 51-minute period from Wednesday, 11 July 2018 at 12:58 UTC to Tuesday, 07 July 2020 at 18:50 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 - thebma
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:
[132] chair,cnagpaul [121] medical,students [114] nhs,staff [109] chair,council [103] find,out [101] council,cnagpaul [93] read,more [84] health,service [83] mental,health [78] healthcare,workers Top Word Pairs in Tweet in G1:
[122] chair,cnagpaul [107] chair,council [101] council,cnagpaul [100] nhs,staff [95] medical,students [85] read,more [84] find,out [74] health,service [72] mental,health [67] doctors,medical Top Word Pairs in Tweet in G2:
[25] medical,students [24] junior,doctors [15] thebma,cnagpaul [13] thebma,survey [12] healthcare,workers [11] cnagpaul,thebma [11] covid,19 [11] looking,forward [10] make,sure [10] thebma,bma_juniordocs Top Word Pairs in Tweet in G3:
[5] patient,care [5] deal,brexit [5] read,thebma [5] thebma,thercn [4] settled,status [4] read,more [4] thebma,bmj_latest [4] health,services [4] thebma,s [3] eu,staff Top Word Pairs in Tweet in G4:
[3] looking,forward [3] east,england [3] thebma,members [2] gender,pay [2] pay,gap [2] please,take [2] home,office [2] england,'women [2] 'women,medicine' [2] medicine',event Top Word Pairs in Tweet in G5:
[4] european,medical [4] british,medicine [4] medicine,european [4] european,medicine [3] bma,scotland [2] chair,lewis [2] lewis,morrison [2] chair,bma [2] consultant,s [2] s,committee Top Word Pairs in Tweet in G6:
[3] speak,thebma [2] organ,donation [2] healthcare,professionals [2] future,policy [2] peoplesvote_uk,rally [2] thursday,afternoon [2] air,pollution [2] risk,assessment Top Word Pairs in Tweet in G7:
[8] south,east [6] bma,org [6] org,uk [4] help,shape [4] bma,member [4] vision,nhs [4] regional,council [3] join,regional [3] 21,02 [3] #nhsfuture,event Top Word Pairs in Tweet in G8:
[10] bma,foundation [5] research,grants [5] find,out [5] out,more [3] click,here [3] here,find [3] thebma,#medicalresearch [3] medical,research [2] covid,19 [2] research,supported Top Word Pairs in Tweet in G9:
[2] nhs,staff [2] sign,up [2] cnagpaul,chair [2] #unlockingthenhs,cancer Top Word Pairs in Tweet in G10:
[3] bame,people [2] ukcp_updates,centreformh [2] centreformh,samaritans [2] timkendall1,rcpsych [2] rcpsych,thebma [2] first,evidence [2] evidence,session [2] cnagpaul,kamleshkhunti [2] kamleshkhunti,plattlucinda [2] plattlucinda,panel Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
Top Replied-To in G4:
Top Replied-To in G5:
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: