The graph represents a network of 1,652 Twitter users whose recent tweets were included in a list (Tweet ID List - @fph network) 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 Monday, 06 July 2020 at 15:11 UTC.
The tweets in the network were tweeted over the 1479-day, 3-hour, 52-minute period from Tuesday, 14 June 2016 at 07:29 UTC to Thursday, 02 July 2020 at 11:22 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 : 1652
Unique Edges : 2837
Edges With Duplicates : 6678
Total Edges : 9515
Self-Loops : 1244
Reciprocated Vertex Pair Ratio : 0.122195269860522
Reciprocated Edge Ratio : 0.217778978654418
Connected Components : 1
Single-Vertex Connected Components : 0
Maximum Vertices in a Connected Component : 1652
Maximum Edges in a Connected Component : 9515
Maximum Geodesic Distance (Diameter) : 2
Average Geodesic Distance : 1.996372
Graph Density : 0.00135694413687207
Modularity : 0.202872
NodeXL Version : 1.0.1.437
Data Import : The graph represents a network of 1,652 Twitter users whose recent tweets were included in a list (Tweet ID List - @fph network) 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 Monday, 06 July 2020 at 15:11 UTC.
The tweets in the network were tweeted over the 1479-day, 3-hour, 52-minute period from Tuesday, 14 June 2016 at 07:29 UTC to Thursday, 02 July 2020 at 11:22 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 - @fph network
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:
[1032] public,health [125] mental,health [114] #donoharm,amendment [110] photo,competition [109] photo,comp [93] looking,forward [92] find,out [89] s,health [87] fph,president [85] well,done Top Word Pairs in Tweet in G1:
[732] public,health [106] photo,comp [88] photo,competition [86] mental,health [78] find,out [78] #donoharm,amendment [77] fph,president [76] read,blog [68] https,t [68] t,co Top Word Pairs in Tweet in G2:
[133] public,health [22] #donoharm,amendment [16] s,health [15] well,done [14] mental,health [13] health,inequalities [12] annual,conference [11] amendment,#euwithdrawalbill [11] fph,conference [10] #pheconf19,fph Top Word Pairs in Tweet in G3:
[39] public,health [31] fph,phe_uk [14] phe_uk,award [9] contributions,public [8] award,contributions [8] ahcsuk,macmillancancer [7] viapathuk,wearechroma [7] wearechroma,scotgovhealth [7] scotgovhealth,allied_health_s [7] allied_health_s,ahcsuk Top Word Pairs in Tweet in G4:
[43] public,health [10] #scotpublichealth,conference [9] life,expectancy [8] julie,cavanagh [7] fph,scotland [7] human,rights [6] looking,forward [6] mental,health [6] fphscot,conference [6] gary,ritchie Top Word Pairs in Tweet in G5:
[12] public,health [6] well,done [6] photo,competition [4] great,see [4] fph,s [4] #publichealthlookslike,photo [3] honorary,membership [3] fph,membership [3] blog,post [2] health,care Top Word Pairs in Tweet in G6:
[12] public,health [3] cardiovascular,disease [3] health,care [3] care,professionals [3] find,out [3] more,here [2] disease,prevention [2] please,share [2] here,fph [2] new,report Top Word Pairs in Tweet in G7:
[18] public,health [14] journal,public [7] fph,journal [3] read,latest [2] mental,health [2] trusselltrust,fph [2] health,explores [2] read,fph [2] zika,vaccine [2] collection,articles Top Word Pairs in Tweet in G8:
[4] health,transport [4] transport,action [4] action,plan [3] evaluating,joint [3] joint,public [3] public,health [3] health,interventions [3] thanks,civitas_eu [3] civitas_eu,nestrans [3] nestrans,support Top Word Pairs in Tweet in G9:
[3] fph,session [3] psychological,support [3] support,community [3] community,resilience [2] sexual,health [2] health,impacts [2] armed,conflict [2] phe_uk,conference [2] psychosocial,support [2] approach,psychological Top Word Pairs in Tweet in G10:
[2] tooth,decay [2] oral,health [2] working,together [2] together,better [2] better,health [2] health,#bascd [2] #bascd,fph [2] fph,looking [2] looking,teeth [2] teeth,especially 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 G6:
Top Replied-To in G7:
Top Replied-To in G8:
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: