The graph represents a network of 33,137 Twitter users whose recent tweets were included in a list (Tweet ID List WAAW and associated 2019) of 73224 tweet IDs, or who were replied to or mentioned in those tweets. 66157 out of 73224 tweets were collected. The network was obtained from Twitter on Tuesday, 04 January 2022 at 03:08 UTC.
The tweets in the network were tweeted over the 1864-day, 1-hour, 6-minute period from Saturday, 18 October 2014 at 11:50 UTC to Monday, 25 November 2019 at 12:56 UTC.
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 : 33137
Unique Edges : 72666
Edges With Duplicates : 52046
Total Edges : 124712
Self-Loops : 9090
Reciprocated Vertex Pair Ratio : 0.0372034395397307
Reciprocated Edge Ratio : 0.0717379794965587
Connected Components : 2162
Single-Vertex Connected Components : 1564
Maximum Vertices in a Connected Component : 29646
Maximum Edges in a Connected Component : 120355
Maximum Geodesic Distance (Diameter) : 14
Average Geodesic Distance : 4.23895
Graph Density : 7.56884413269483E-05
Modularity : 0.488861
NodeXL Version : 1.0.1.449
Data Import : The graph represents a network of 33,137 Twitter users whose recent tweets were included in a list (Tweet ID List WAAW and associated 2019) of 73224 tweet IDs, or who were replied to or mentioned in those tweets. 66157 out of 73224 tweets were collected. The network was obtained from Twitter on Tuesday, 04 January 2022 at 03:08 UTC.
The tweets in the network were tweeted over the 1864-day, 1-hour, 6-minute period from Saturday, 18 October 2014 at 11:50 UTC to Monday, 25 November 2019 at 12:56 UTC.
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 : TwitterIDList
Graph Term : Tweet ID List WAAW and associated 2019
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:
[10370] awareness,week [9962] antibiotic,awareness [7322] world,antibiotic [5058] antibiotic,resistance [5049] use,antibiotics [3798] future,#antibiotics [3788] #antibiotics,depends [3291] week,world [3235] global,threat [3152] rise,#antibioticresistance Top Word Pairs in Tweet in G1:
[3589] awareness,week [3098] antibiotic,awareness [3020] world,antibiotic [2816] future,#antibiotics [2810] #antibiotics,depends [2360] rise,#antibioticresistance [2346] use,antibiotics [2315] week,rise [2084] week,world [2080] global,threat Top Word Pairs in Tweet in G2:
[1931] awareness,week [1918] antibiotic,awareness [1167] world,antibiotic [1008] antibiotic,resistance [844] drug,resistant [724] antibiotic,use [603] find,out [585] antimicrobial,resistance [527] use,antibiotics [512] global,health Top Word Pairs in Tweet in G3:
[1108] antibiotic,awareness [749] #eaad2019,#keepantibioticsworking [742] awareness,week [680] uso,prudente [605] #eaad,#eaad2019 [601] world,antibiotic [535] use,antibiotics [518] awareness,day [515] https,t [515] t,co Top Word Pairs in Tweet in G4:
[782] awareness,week [726] antibiotic,resistance [700] antibiotic,awareness [626] learn,more [503] 35,000 [474] use,antibiotics [460] 000,deaths [444] 15,minutes [423] #antibioticresistance,s [422] deaths,year Top Word Pairs in Tweet in G5:
[431] antibiotic,awareness [418] awareness,week [251] antibiotic,resistance [236] world,antibiotic [173] matches,personality [172] antibiotic,best [172] best,matches [170] #beantibioticsaware,#antibioticawarenessweek [169] #antibioticawarenessweek,antibiotic [77] u,s Top Word Pairs in Tweet in G6:
[606] awareness,week [337] antibiotic,awareness [289] use,antibiotics [259] world,antibiotic [258] #amractionng,#waaw2019 [234] antibiotics,awareness [221] antibiotic,resistance [179] #naaw2019,#amractionng [131] global,health [121] world,antibiotics Top Word Pairs in Tweet in G7:
[590] uso,indebido [343] sobre,uso [325] superbacterias,pueden [281] uso,antibióticos [277] usa,antibióticos [241] curar,infecciones [234] pone,riesgo [222] resistencia,antibióticos [222] amenaza,salud [216] indebido,antibióticos Top Word Pairs in Tweet in G8:
[437] antibiotic,awareness [381] awareness,week [348] world,antibiotic [324] antibiotic,resistance [260] find,out [227] taking,antibiotics [206] help,tackle [202] always,take [162] week,find [159] need,puts Top Word Pairs in Tweet in G9:
[536] alexander,fleming [408] 1928,alexander [408] fleming,discovered [408] discovered,mould [408] mould,working [408] working,produced [408] produced,substance [408] substance,kill [408] kill,many [408] many,common Top Word Pairs in Tweet in G10:
[671] kerintangan,antibiotik [632] jika,anda [529] tidak,mampu [316] anda,demam [316] demam,biasa [316] biasa,atau [316] atau,demam [316] demam,denggi [316] denggi,selesema [316] selesema,atau Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Replied-To in G5:
Top Replied-To in G6:
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Top Replied-To in G8:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
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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:
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Top Tweeters in G5:
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Top Tweeters in G8:
Top Tweeters in G9:
Top Tweeters in G10: