The graph represents a network of 7,214 Twitter users whose recent tweets were included in a list (Tweet ID List #AG #KAW 2019 (adding missing RTs)) of 13116 tweet IDs, or who were replied to or mentioned in those tweets. 13092 out of 13116 tweets were collected. The network was obtained from Twitter on Monday, 17 January 2022 at 15:47 UTC.
The tweets in the network were tweeted over the 6-day, 19-hour, 42-minute period from Monday, 18 November 2019 at 01:37 UTC to Sunday, 24 November 2019 at 21:19 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 : 7214
Unique Edges : 15413
Edges With Duplicates : 11768
Total Edges : 27181
Self-Loops : 1682
Reciprocated Vertex Pair Ratio : 0.0487704918032787
Reciprocated Edge Ratio : 0.0930050801094177
Connected Components : 337
Single-Vertex Connected Components : 176
Maximum Vertices in a Connected Component : 6345
Maximum Edges in a Connected Component : 25963
Maximum Geodesic Distance (Diameter) : 14
Average Geodesic Distance : 4.390519
Graph Density : 0.000344251828524346
Modularity : 0.507545
NodeXL Version : 1.0.1.449
Data Import : The graph represents a network of 7,214 Twitter users whose recent tweets were included in a list (Tweet ID List #AG #KAW 2019 (adding missing RTs)) of 13116 tweet IDs, or who were replied to or mentioned in those tweets. 13092 out of 13116 tweets were collected. The network was obtained from Twitter on Monday, 17 January 2022 at 15:47 UTC.
The tweets in the network were tweeted over the 6-day, 19-hour, 42-minute period from Monday, 18 November 2019 at 01:37 UTC to Sunday, 24 November 2019 at 21:19 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 : TwitterIDList
Graph Term : Tweet ID List #AG #KAW 2019 (adding missing RTs)
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:
[1260] antibiotic,awareness [899] antibiotic,use [866] more,work [861] awareness,week [858] #eaad2019,#keepantibioticsworking [840] find,out [745] role,play [744] antibiotic,resistance [722] #keepantibioticsworking,#antibioticresistance [684] #antibioticguardian,#keepantibioticsworking Top Word Pairs in Tweet in G1:
[345] awareness,week [332] antibiotic,awareness [324] #antibioticguardian,#keepantibioticsworking [321] #keepantibioticsworking,#antibioticguardian [284] find,out [260] #waaw2019,#antibioticguardian [257] #antibioticguardian,#waaw2019 [255] global,health [243] one,urgent [243] urgent,global Top Word Pairs in Tweet in G2:
[301] antibiotic,awareness [245] awareness,day [223] #keepantibioticsworking,#eaad [204] role,play [165] use,antibiotics [164] everyone,role [156] use,#antibiotics [147] #keepantibioticsworking,#antibioticresistance [143] antibiotic,resistance [142] #antibioticresistance,#keepantibioticsworking Top Word Pairs in Tweet in G3:
[660] #eaad2019,#keepantibioticsworking [388] #eaad,#eaad2019 [376] uso,prudente [359] #keepantibioticsworking,#antibioticresistance [290] prudente,antibióticos [279] #pranamr19,#eaad2019 [227] #antibioticresistance,#amr [219] día,europeo [214] europeo,uso [210] antibiotics,effective Top Word Pairs in Tweet in G4:
[792] more,work [410] #amr,#waaw2019 [403] antibiotic,use [402] learn,more [396] #antimicrobialresistance,doing [396] doing,fight [396] fight,antibiotic [396] use,reduced [396] reduced,20 [396] 20,past Top Word Pairs in Tweet in G5:
[149] taking,antibiotics [145] always,take [142] help,#keepantibioticsworking [109] t,always [109] sore,throats [108] aren,t [108] feel,unwell [107] antibiotics,aren [107] always,needed [107] needed,feel Top Word Pairs in Tweet in G6:
[129] antibiotic,awareness [110] #keepantibioticsworking,#stopsuperbugs [95] #stopsuperbugs,#antibioticguardian [95] find,out [87] world,antibiotic [86] awareness,week [62] #antibioticresistance,#keepantibioticsworking [59] #waaw2019,#keepantibioticsworking [58] #involveyoungpeople,#keepantibioticsworking [57] #waaw2019,#antibioticresistance Top Word Pairs in Tweet in G7:
[93] degli,#antibiotici [73] consapevole,degli [61] #keepantibioticsworking,#waaw2019 [58] giornata,europea [53] #18novembre,giornata [53] gli,antibiotici [51] settimana,mondiale [50] degli,antibiotici [46] diretta,#keepantibioticsworking [44] agli,antibiotici Top Word Pairs in Tweet in G8:
[39] #antibioticguardian,#keepantibioticsworking [35] pledged,#antibioticguardian [35] actions,protect [35] protect,#antibiotics [35] #antibiotics,join [31] #keepantibioticsworking,actions [29] antibiotic,resistance [22] taking,antibiotics [19] find,out [17] need,puts Top Word Pairs in Tweet in G9:
[122] global,health [112] raising,awareness [110] health,threat [108] #amr,#diagnosticsispower [104] antimicrobial,resistance [104] role,play [102] #keepantibioticsworking,#amr [101] resistance,become [101] become,global [101] threat,raising Top Word Pairs in Tweet in G10:
[31] #amr,#ams [30] fight,#antibioticresistance [28] #waaw,#antibioticguardian [25] #handhygiene,simple [25] simple,cost [25] cost,effective [25] effective,s [25] s,effective [25] effective,intervention [25] intervention,reduce 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 G4:
Top Replied-To in G5:
Top Replied-To in G6:
Top Replied-To in G8:
Top Replied-To in G9:
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 G4:
Top Mentioned in G5:
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: