The graph represents a network of 258 Twitter users whose recent tweets contained "#euphaateph2019", 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 Monday, 25 November 2019 at 08:38 UTC.
The tweets in the network were tweeted over the 8-day, 8-hour, 13-minute period from Saturday, 16 November 2019 at 10:26 UTC to Sunday, 24 November 2019 at 18:39 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 : 258
Unique Edges : 909
Edges With Duplicates : 619
Total Edges : 1528
Self-Loops : 35
Reciprocated Vertex Pair Ratio : 0.0822596630327057
Reciprocated Edge Ratio : 0.152014652014652
Connected Components : 6
Single-Vertex Connected Components : 0
Maximum Vertices in a Connected Component : 230
Maximum Edges in a Connected Component : 1449
Maximum Geodesic Distance (Diameter) : 5
Average Geodesic Distance : 2.2489
Graph Density : 0.0164690978192019
Modularity : 0.322409
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 258 Twitter users whose recent tweets contained "#euphaateph2019", 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 Monday, 25 November 2019 at 08:38 UTC.
The tweets in the network were tweeted over the 8-day, 8-hour, 13-minute period from Saturday, 16 November 2019 at 10:26 UTC to Sunday, 24 November 2019 at 18:39 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 : #euphaateph2019
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:
[252] #eph2019,#euphaateph2019 [214] public,health [145] #euphaateph2019,#eph2019 [29] knowledge,translation [28] digitalization,potentials [28] potentials,pitfalls [28] pitfalls,public [28] health,perspective [28] #euphaateph2019,#digitalhealth [28] bridges,between Top Word Pairs in Tweet in G1:
[81] #eph2019,#euphaateph2019 [56] #euphaateph2019,#eph2019 [53] public,health [19] digital,health [15] join,network [14] health,promotion [14] pre,conferences [13] look,forward [12] health,join [12] network,session Top Word Pairs in Tweet in G2:
[55] #eph2019,#euphaateph2019 [41] public,health [18] #euphaateph2019,#eph2019 [16] eu_health,eu_commission [15] health,priorities [15] priorities,eu_health [15] eu_commission,1 [15] 1,antimicrobial [15] antimicrobial,resistance [15] resistance,2 Top Word Pairs in Tweet in G3:
[45] public,health [44] #eph2019,#euphaateph2019 [22] #euphaateph2019,#eph2019 [15] soft,skills [13] generation,public [11] skills,next [11] next,generation [11] health,professionals [11] professionals,need [11] need,sara_mcquinn Top Word Pairs in Tweet in G4:
[47] #euphaateph2019,#eph2019 [41] #eph2019,#euphaateph2019 [27] public,health [18] bekker_mpm,eph_phppsection [14] knowledge,translation [10] sections,#euphaateph2019 [10] translation,evidence [10] evidence,informed [10] informed,policymaking [10] #evipnet,who_europe Top Word Pairs in Tweet in G5:
[41] public,health [29] #eph2019,#euphaateph2019 [19] good,news [19] news,continue [19] continue,supplement [19] supplement,european [19] european,journal [19] journal,public [19] health,out [19] out,digitalization Top Word Pairs in Tweet in G6:
[11] ird_fr,coalitionplus [9] daniel,simões [9] simões,gatvih [9] community,based [9] based,research [9] #euphaateph2019,ird_fr [6] jordi,casabona [6] casabona,ceeiscat [6] ceeiscat,daniel [6] gatvih,present Top Word Pairs in Tweet in G7:
[8] présentation,2 [8] 2,outils [8] outils,#etp [8] #etp,à [8] à,#euphaateph2019 [8] #euphaateph2019,comète [8] comète,etp [8] etp,scène [8] scène,cres_paca [2] cres_paca,#euphaateph2019 Top Word Pairs in Tweet in G8:
[5] scottlgreer,eu [5] eu,huge [5] huge,ability [5] ability,affect [5] affect,health [5] health,through [5] through,public [5] public,health [5] health,powers [5] powers,through Top Word Pairs in Tweet in G9:
[5] alessio_corradi,#euphaateph2019 [5] #euphaateph2019,best [5] best,poster [5] poster,#igienetorino [5] #igienetorino,congratulations [5] congratulations,bert_fabrizio [5] bert_fabrizio,mrgualano Top Word Pairs in Tweet in G10:
[6] santé,publique [4] arrivée,matinale [4] matinale,sur [4] sur,site [4] site,palais [4] palais,des [4] des,événements [4] événements,#marseille [4] #marseille,12e [4] 12e,conférence Top Replied-To in Entire Graph:
Top Replied-To in G2:
Top Replied-To in G3:
Top Replied-To in G6:
Top Replied-To in G7:
Top Replied-To in G8:
Top Replied-To in G9:
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 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: