The graph represents a network of 2,728 Twitter users whose recent tweets contained "#ECCMID2019 OR #ECCMID19 OR #ECCMID", 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 Sunday, 14 April 2019 at 17:56 UTC.
The tweets in the network were tweeted over the 9-day, 19-hour, 8-minute period from Thursday, 04 April 2019 at 22:38 UTC to Sunday, 14 April 2019 at 17:46 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 : 2728
Unique Edges : 8274
Edges With Duplicates : 7450
Total Edges : 15724
Self-Loops : 1721
Reciprocated Vertex Pair Ratio : 0.0493302147565384
Reciprocated Edge Ratio : 0.0940222897669706
Connected Components : 150
Single-Vertex Connected Components : 105
Maximum Vertices in a Connected Component : 2486
Maximum Edges in a Connected Component : 15397
Maximum Geodesic Distance (Diameter) : 11
Average Geodesic Distance : 3.658574
Graph Density : 0.00132674557778358
Modularity : 0.360718
NodeXL Version : 1.0.1.410
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[301] infectious,diseases [259] pk,pd [216] critically,ill [213] stand,1 [209] ill,patients [190] 1,3 [183] booth,1 [180] #eccmid2019,escmid [155] antibiotic,use [151] learn,more Top Word Pairs in Tweet in G1:
[191] pk,pd [164] 1,3 [135] infectious,diseases [132] critically,ill [126] ill,patients [124] stand,1 [95] year,#infectiousdiseases [93] #infectiousdiseases,#eccmid2019 [75] acquired,pneumonia [67] #fungal,#infections Top Word Pairs in Tweet in G2:
[56] went,school [42] infectious,diseases [39] biofilms,vivo [36] background,reading [36] higher,mutation [35] antibiotic,treatment [32] thus,develop [32] develop,resistance [31] michiels,shows [31] shows,persisters Top Word Pairs in Tweet in G3:
[68] register,now [65] antibiotic,use [62] hand,hygiene [62] antibiotic,resistance [58] antibiotic,stewardship [51] #eccmid2019,1healthau [48] thelancetinfdis,paper [48] paper,published [48] published,reductions [48] reductions,cauti Top Word Pairs in Tweet in G4:
[99] #eccmid2019,escmid [58] antimicrobial,resistance [57] #jac,amr [54] jac,amr [54] peer,reviewed [51] online,journal [49] amr,#openaccess [49] #openaccess,online [49] journal,revolutionise [49] revolutionise,way Top Word Pairs in Tweet in G5:
[9] booth,1 [8] looking,forward [8] #eccmid2019,amsterdam [7] infectious,diseases [5] stand,1 [4] clinical,microbiology [4] microbiology,infectious [4] chronic,bone [3] 13,16 [3] learn,more Top Word Pairs in Tweet in G6:
[14] infectious,diseases [13] #eccmid2019,thlorg [12] associated,infections [12] session,starts [11] #healthcare,associated [11] #climatechange,infectious [10] 90,90 [10] long,acting [10] ecdc,expert [9] hall,j Top Word Pairs in Tweet in G7:
[24] booth,1 [24] learn,more [23] hall,g [21] roche,#eccmid2019 [17] join,roche [17] #eccmid2019,symposium [17] symposium,convergence [17] convergence,phenotypic [17] phenotypic,genotypic [17] genotypic,biomarkers Top Word Pairs in Tweet in G8:
[20] mikemorrison,paulsaxmd [17] bold,new [17] new,poster [17] poster,format [17] format,#eccmid2019 [17] #eccmid2019,h [17] h,t [17] t,mikemorrison [17] paulsaxmd,#betterposter [17] #betterposter,#cdiff Top Word Pairs in Tweet in G9:
[52] stand,1 [39] 1,112 [24] #eccmid2019,walesmicrobiol [22] 1,124 [18] microbiology,publichealthw [18] job,opportunities [18] #eccmid2019,stand [17] walesmicrobiol,#eccmid2019 [16] visit,stand [14] come,visit Top Word Pairs in Tweet in G10:
[19] healthcare,associated [14] associated,#infections [11] resistant,bacterial [11] #eccmid2019,#infectiousdisease [10] #infezioninosocomiali,#eccmid2019 [9] nosocomiali,sono [9] #infectiousdisease,threats [9] threats,#inventingforlife [8] #dyk,risk [8] risk,factors Top Replied-To in Entire Graph:
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Top Mentioned in Entire Graph:
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Top Tweeters in Entire Graph:
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Top Tweeters in G10: