The graph represents a network of 1,351 Twitter users whose recent tweets contained "#EPH2019", 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 Saturday, 23 November 2019 at 20:54 UTC.
The tweets in the network were tweeted over the 9-day, 8-hour, 10-minute period from Thursday, 14 November 2019 at 12:38 UTC to Saturday, 23 November 2019 at 20:48 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 : 1351
Unique Edges : 5105
Edges With Duplicates : 6918
Total Edges : 12023
Self-Loops : 607
Reciprocated Vertex Pair Ratio : 0.117491749174917
Reciprocated Edge Ratio : 0.210277613703485
Connected Components : 29
Single-Vertex Connected Components : 21
Maximum Vertices in a Connected Component : 1311
Maximum Edges in a Connected Component : 11972
Maximum Geodesic Distance (Diameter) : 8
Average Geodesic Distance : 3.007253
Graph Density : 0.00371302464566713
Modularity : 0.288893
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 1,351 Twitter users whose recent tweets contained "#EPH2019", 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 Saturday, 23 November 2019 at 20:54 UTC.
The tweets in the network were tweeted over the 9-day, 8-hour, 10-minute period from Thursday, 14 November 2019 at 12:38 UTC to Saturday, 23 November 2019 at 20:48 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 : #EPH2019
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:
[862] public,health [242] #eph2019,#euphaateph2019 [239] ephconference,#eph2019 [207] #eph2019,ephconference [148] #eph2019,euphacts [140] #euphaateph2019,#eph2019 [118] digital,health [115] health,inequalities [112] looking,forward [109] santé,publique Top Word Pairs in Tweet in G1:
[420] public,health [146] #eph2019,#euphaateph2019 [80] digital,health [74] ephconference,#eph2019 [74] #eph2019,euphacts [65] #euphaateph2019,#eph2019 [57] 11,10 [56] looking,forward [50] #eph2019,ephconference [48] health,policies Top Word Pairs in Tweet in G2:
[110] public,health [80] ephconference,#eph2019 [42] #eph2019,ephconference [35] check,out [23] #eph2019,marseille [22] #eph2019,#ephfellow [21] here,#eph2019 [20] health,inequalities [19] health,services [18] springernature,booth Top Word Pairs in Tweet in G3:
[98] public,health [94] santé,publique [36] européenne,santé [33] maison,france [30] conférence,européenne [27] #eph2019,ephconference [23] sur,pont [23] à,marseille [23] euphacts,sfspasso [22] publique,#eph2019 Top Word Pairs in Tweet in G4:
[118] public,health [61] #eph2019,#euphaateph2019 [55] #euphaateph2019,#eph2019 [41] #eph2019,euphacts [28] life,expectancy [28] ihme_uw,#eph2019 [19] nordic,countries [18] finland,iceland [18] new,#gbdstudy [17] ephconference,#eph2019 Top Word Pairs in Tweet in G5:
[57] #eph2019,ephconference [43] public,health [42] health,inequalities [27] ephconference,#eph2019 [22] lucinda,hiam [19] infant,mortality [19] deaths,despair [16] #eph2019,plenary [13] otto,scharmer [13] european,countries Top Word Pairs in Tweet in G6:
[20] social,care [16] public,health [16] health,social [15] migrants,#eph2019 [15] #eph2019,euphacts [14] uk,infant [14] infant,mortality [14] mortality,rises [14] rises,last [14] last,3 Top Word Pairs in Tweet in G7:
[18] health,information [12] public,health [12] pre,conference [12] environmental,#burdenofdisease [11] #eph2019,phmrsection [10] #eph2019,ephconference [9] #eph2019,#burdeneu [8] don,t [8] rki_de,marikentijhuis [8] learn,more Top Word Pairs in Tweet in G8:
[29] #dph2019,#eph2019 [15] #eph2019,#dph2019 [13] #publichealth,#digitalhealth [13] danielapaolotti,isi_fondazione [12] #eph2019,#digitalinnovation [11] #digitalhealth,#publichealth [11] #digitalinnovation,#publichealth [7] rod33470,univbordeaux [7] univbordeaux,dphgraduateprog [7] daniela,paolotti Top Word Pairs in Tweet in G9:
[19] social,biological [17] workshop,social [17] processes,over [17] over,lifecourse [15] biological,processes [15] based,lifepath_eu [14] lifepath_eu,social2bio [12] social,inequalities [10] lifecourse,social [10] 14,50 Top Word Pairs in Tweet in G10:
[4] public,health [3] pre,conference [3] looking,forward [2] climate,change [2] #eph2019,conference [2] out,#eph2019 [2] #eph2019,plenary Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Replied-To in G7:
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Top Replied-To in G9:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Tweeters in Entire Graph:
Top Tweeters in G1:
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Top Tweeters in G4:
Top Tweeters in G5:
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Top Tweeters in G9:
Top Tweeters in G10: