The graph represents a network of 9,309 Twitter users whose recent tweets contained "#AntibioticResistance since:2019-11-18 until:2019-11-19", 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 Tuesday, 19 November 2019 at 15:44 UTC.
The tweets in the network were tweeted over the 23-hour, 57-minute period from Monday, 18 November 2019 at 00:00 UTC to Monday, 18 November 2019 at 23:58 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 : 9309
Unique Edges : 14210
Edges With Duplicates : 3587
Total Edges : 17797
Self-Loops : 1412
Reciprocated Vertex Pair Ratio : 0.0150640574405181
Reciprocated Edge Ratio : 0.0296809986130374
Connected Components : 737
Single-Vertex Connected Components : 489
Maximum Vertices in a Connected Component : 7925
Maximum Edges in a Connected Component : 16228
Maximum Geodesic Distance (Diameter) : 13
Average Geodesic Distance : 3.967131
Graph Density : 0.000166420129440238
Modularity : 0.649173
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 9,309 Twitter users whose recent tweets contained "#AntibioticResistance since:2019-11-18 until:2019-11-19", 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 Tuesday, 19 November 2019 at 15:44 UTC.
The tweets in the network were tweeted over the 23-hour, 57-minute period from Monday, 18 November 2019 at 00:00 UTC to Monday, 18 November 2019 at 23:58 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 : #AntibioticResistance since:2019-11-18 until:2019-11-19
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:
[3118] awareness,week [2638] antibiotic,awareness [2351] use,antibiotics [2279] future,#antibiotics [2276] #antibiotics,depends [2274] world,antibiotic [2264] rise,#antibioticresistance [2223] week,rise [2084] global,threat [1901] week,world Top Word Pairs in Tweet in G1:
[1878] awareness,week [1851] rise,#antibioticresistance [1838] week,rise [1833] future,#antibiotics [1833] #antibiotics,depends [1523] antibiotic,awareness [1521] world,antibiotic [1507] global,threat [1507] use,antibiotics [1506] #antibioticresistance,global Top Word Pairs in Tweet in G2:
[307] antibiotic,resistance [296] antibiotic,use [296] one,urgent [295] health,threats [281] improving,antibiotic [271] everyone,role [269] role,play [257] global,health [256] #antibioticresistance,#usaaw19 [248] help,fight Top Word Pairs in Tweet in G3:
[333] role,play [308] everyone,role [307] global,health [282] urgent,global [271] one,urgent [269] health,threats [232] antibiotic,resistance [227] threats,everyone [200] find,out [193] help,fight Top Word Pairs in Tweet in G4:
[223] global,threat [204] 10,million [202] antimicrobial,resistance [202] resistance,global [202] threat,estimated [202] estimated,consequences [202] consequences,inaction [202] inaction,lead [202] lead,10 [202] million,deaths Top Word Pairs in Tweet in G5:
[437] due,#antibioticresistance [435] 15,minutes [435] minutes,one [435] one,person [435] person,dies [435] dies,infection [435] infection,antibiotics [435] antibiotics,longer [435] longer,treat [435] treat,effectively Top Word Pairs in Tweet in G6:
[481] drug,resistant [480] here's,addressing [480] addressing,#antibioticresistance [480] #antibioticresistance,everyone's [480] everyone's,responsibility [480] responsibility,drug [480] resistant,bacteria [480] bacteria,found [480] found,everywhere [480] everywhere,community Top Word Pairs in Tweet in G7:
[60] antibiotic,resistance [48] everyone,role [47] role,play [43] global,health [42] antibiotic,awareness [42] improving,antibiotic [41] help,fight [40] awareness,week [39] antibiotic,use [36] use,help Top Word Pairs in Tweet in G8:
[324] #eaad,#eaad2019 [321] #eaad2019,#keepantibioticsworking [304] #keepantibioticsworking,#antibioticresistance [216] #antibioticresistance,#amr [199] don,t [199] cold,flu [198] antibiotics,effective [197] effective,against [197] against,viral [197] viral,infections Top Word Pairs in Tweet in G9:
[145] awareness,week [144] #antibiotics,puts [135] antibiotic,awareness [132] world,antibiotic [110] misuse,overuse [110] resistant,antibiotics [108] everyone,risk [108] #antibioticresistance,happens [108] happens,bacteria [108] bacteria,evolve Top Word Pairs in Tweet in G10:
[209] #antibioticresistance,apocalypse [208] facing,#antibioticresistance [13] #antibioticresistance,growing [13] growing,global [13] global,public [13] public,health [13] health,threat [13] threat,meet [13] meet,teams [13] teams,fighting Top Replied-To in Entire Graph:
Top Replied-To in G2:
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Top Replied-To in G6:
Top Replied-To in G8:
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Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
Top Mentioned in G2:
Top Mentioned in G3:
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Top Mentioned in G6:
Top Mentioned in G7:
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Top Mentioned in G9:
Top Mentioned in G10:
Top Tweeters in Entire Graph:
Top Tweeters in G1:
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Top Tweeters in G3:
Top Tweeters in G4:
Top Tweeters in G5:
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Top Tweeters in G7:
Top Tweeters in G8:
Top Tweeters in G9:
Top Tweeters in G10: