The graph represents a network of 6,615 Twitter users whose recent tweets contained "#eaad OR #eaad2019 OR #eaad19 OR #waaw OR #waaw19 OR #waaw2019 OR #antibioticawareness OR #worldantibioticawarenessweek OR #antibioticawarenessweek OR "antibiotic awareness week" OR "antibiotic awareness day" OR #stopsuperbugs OR #aaw2019 OR #aaw19 OR #antibioticguardian OR #keepantibioticsworking OR #antibioticresistance since:2019-11-21 until:2019-11-22", 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 Friday, 22 November 2019 at 16:43 UTC.
The tweets in the network were tweeted over the 23-hour, 59-minute period from Thursday, 21 November 2019 at 00:00 UTC to Thursday, 21 November 2019 at 23:59 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 : 6615
Unique Edges : 12409
Edges With Duplicates : 4962
Total Edges : 17371
Self-Loops : 1569
Reciprocated Vertex Pair Ratio : 0.0370341124447252
Reciprocated Edge Ratio : 0.0714231325668164
Connected Components : 718
Single-Vertex Connected Components : 363
Maximum Vertices in a Connected Component : 4971
Maximum Edges in a Connected Component : 15192
Maximum Geodesic Distance (Diameter) : 16
Average Geodesic Distance : 4.913279
Graph Density : 0.000300171810820219
Modularity : 0.62108
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 6,615 Twitter users whose recent tweets contained "#eaad OR #eaad2019 OR #eaad19 OR #waaw OR #waaw19 OR #waaw2019 OR #antibioticawareness OR #worldantibioticawarenessweek OR #antibioticawarenessweek OR "antibiotic awareness week" OR "antibiotic awareness day" OR #stopsuperbugs OR #aaw2019 OR #aaw19 OR #antibioticguardian OR #keepantibioticsworking OR #antibioticresistance since:2019-11-21 until:2019-11-22", 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 Friday, 22 November 2019 at 16:43 UTC.
The tweets in the network were tweeted over the 23-hour, 59-minute period from Thursday, 21 November 2019 at 00:00 UTC to Thursday, 21 November 2019 at 23:59 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 : #eaad OR #eaad2019 OR #eaad19 OR #waaw OR #waaw19 OR #waaw2019 OR #antibioticawareness OR #worldantibioticawarenessweek OR #antibioticawarenessweek OR "antibiotic awareness week" OR "antibiotic awareness day" OR #stopsuperbugs OR #aaw2019 OR #aaw19 OR #antibioticguardian OR #keepantibioticsworking OR #antibioticresistance since:2019-11-21 until:2019-11-22
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:
[1162] awareness,week [1046] antibiotic,awareness [840] world,antibiotic [586] use,antibiotics [458] antibiotic,resistance [414] antimicrobial,resistance [403] future,#antibiotics [403] #antibiotics,depends [374] global,threat [363] drug,resistant Top Word Pairs in Tweet in G1:
[254] antibiotics,used [249] become,resistant [212] drug,resistant [209] misuse,#antibiotics [207] overuse,misuse [204] resistant,infections [204] used,treat [196] #antibiotics,put [196] everyone,risk [196] #antibioticresistance,happens Top Word Pairs in Tweet in G2:
[428] awareness,week [368] antibiotic,awareness [350] world,antibiotic [294] use,antibiotics [275] future,#antibiotics [275] #antibiotics,depends [272] rise,#antibioticresistance [271] week,rise [268] week,world [264] global,threat Top Word Pairs in Tweet in G3:
[88] antibiotic,awareness [86] awareness,week [71] learn,more [66] antibiotic,use [62] #antibioticawarenessweek,#antibioticresistance [59] anyone,seen [59] seen,antibiotic [59] antibiotic,characters [59] characters,lurking [59] lurking,around Top Word Pairs in Tweet in G4:
[76] awareness,week [71] antibiotic,awareness [48] antibiotic,resistance [44] #beantibioticsaware,#antibioticawarenessweek [44] #antibioticawarenessweek,antibiotic [44] world,antibiotic [43] best,matches [43] matches,personality [42] antibiotic,best [19] learn,more Top Word Pairs in Tweet in G5:
[272] 1928,alexander [272] alexander,fleming [272] fleming,discovered [272] discovered,mould [272] mould,working [272] working,produced [272] produced,substance [272] substance,kill [272] kill,many [272] many,common Top Word Pairs in Tweet in G6:
[34] antimicrobial,stewardship [28] delighted,offering [28] offering,free [28] free,antimicrobial [28] stewardship,training [28] training,pharmacists [28] pharmacists,england [28] england,great [28] great,partnership [28] partnership,between Top Word Pairs in Tweet in G7:
[31] awareness,week [24] antibiotic,awareness [24] #waaw2019,#stopsuperbugs [22] find,out [18] out,more [17] world,antibiotic [17] chance,win [13] infection,prevention [13] prevention,control [13] public,health Top Word Pairs in Tweet in G8:
[218] more,work [113] learn,more [110] #amr,#waaw2019 [109] #antimicrobialresistance,doing [109] doing,fight [109] fight,antibiotic [109] antibiotic,use [109] use,reduced [109] reduced,20 [109] 20,past Top Word Pairs in Tweet in G9:
[28] #antimicrobialresistance,global [28] one,health [26] global,#healthsecurity [26] #healthsecurity,risk [26] #health4all,expert [26] expert,tavafia [26] health,approach [26] approach,#amr [26] #antibioticsawarenessweek,#waaw2019 [24] tavafia,reactgroup's Top Word Pairs in Tweet in G10:
[20] awareness,week [19] antibiotic,awareness [19] hqscnz,pharmacnz [19] pharmacnz,pharmsocnz [17] antibiotic,resistance [17] #antibioticresistance,hqscnz [15] #keepantibioticsworking,#antibioticresistance [15] help,#keepantibioticsworking [14] don,t [14] #aaw2019,#antibioticresistance 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 G6:
Top Replied-To in G7:
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 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: