The graph represents a network of 4,281 Twitter users whose recent tweets contained "sugartax", or who were replied to, mentioned, retweeted or quoted in those tweets, taken from a data set limited to a maximum of 5,000 tweets, tweeted between 3/26/2006 12:00:00 AM and 1/14/2023 5:00:35 PM. The network was obtained from Twitter on Sunday, 15 January 2023 at 17:13 UTC.
The tweets in the network were tweeted over the 3095-day, 9-hour, 53-minute period from Thursday, 24 July 2014 at 09:13 UTC to Friday, 13 January 2023 at 19:07 UTC.
There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, an edge for each "retweet" relationship in a tweet, an edge for each "quote" relationship in a tweet, an edge for each "mention in retweet" relationship in a tweet, an edge for each "mention in reply-to" relationship in a tweet, an edge for each "mention in quote" relationship in a tweet, an edge for each "mention in quote reply-to" relationship in a tweet, and a self-loop edge for each tweet that is not from above.
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 : 4281
Unique Edges : 3289
Edges With Duplicates : 8286
Total Edges : 11575
Number of Edge Types : 9
Retweet : 2851
MentionsInRetweet : 4026
Mentions : 1086
Replies to : 691
MentionsInReplyTo : 1093
Tweet : 1224
Quote : 244
MentionsInQuote : 246
MentionsInQuoteReply : 114
Self-Loops : 1701
Reciprocated Vertex Pair Ratio : 0.0402097902097902
Reciprocated Edge Ratio : 0.0773109243697479
Connected Components : 739
Single-Vertex Connected Components : 395
Maximum Vertices in a Connected Component : 1982
Maximum Edges in a Connected Component : 6232
Maximum Geodesic Distance (Diameter) : 16
Average Geodesic Distance : 5.829176
Graph Density : 0.000292260739149513
Modularity : 0.455317
NodeXL Version : 1.0.1.508
Data Import : The graph represents a network of 4,281 Twitter users whose recent tweets contained "sugartax", or who were replied to, mentioned, retweeted or quoted in those tweets, taken from a data set limited to a maximum of 5,000 tweets, tweeted between 3/26/2006 12:00:00 AM and 1/14/2023 5:00:35 PM. The network was obtained from Twitter on Sunday, 15 January 2023 at 17:13 UTC.
The tweets in the network were tweeted over the 3095-day, 9-hour, 53-minute period from Thursday, 24 July 2014 at 09:13 UTC to Friday, 13 January 2023 at 19:07 UTC.
There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, an edge for each "retweet" relationship in a tweet, an edge for each "quote" relationship in a tweet, an edge for each "mention in retweet" relationship in a tweet, an edge for each "mention in reply-to" relationship in a tweet, an edge for each "mention in quote" relationship in a tweet, an edge for each "mention in quote reply-to" relationship in a tweet, and a self-loop edge for each tweet that is not from above.
Layout Algorithm : The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.
Graph Source : TwitterSearch2
Graph Term : sugartax
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 : Betweenness Centrality
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[403] sugar,tax [239] #sugartax,#plastictax [234] sugary,drinks [184] sugar,sweetened [163] sugar,salt [156] soft,drinks [150] south,africa [145] nel,2022 [137] #plastictax,#sugartax [133] 2022,grazie Top Word Pairs in Tweet in G1:
[58] sugar,tax [50] soft,drinks [31] industry,levy [23] uk,#sugartax [21] uk,soft [19] things,know [19] know,food_strategy [17] soft,drink [17] artificial,sweeteners [16] drink,industry Top Word Pairs in Tweet in G2:
[83] sugar,tax [25] sugar,salt [19] #sugartax,#salttax [16] tax,sugar [15] soft,drinks [11] south,africa [11] liz,truss [10] #sugartax,#obesity [10] sugary,drinks [9] #plastictax,#sugartax Top Word Pairs in Tweet in G3:
[112] assobibe,#sugartax [80] delle,bevande [79] #plastictax,#sugartax [71] #sugartax,tassa [70] bevande,analcoliche [69] #sugartax,#plastictax [67] buon,senso [58] imprese,settore [54] delle,imprese [53] vigore,#sugartax Top Word Pairs in Tweet in G4:
[139] sugary,drinks [128] south,africa [70] coke,south [70] craving,coke [68] promotion,levy [64] #sugartax,counter [64] counter,addictive [64] used,#sugartax [64] africa,used [64] addictive,nature Top Word Pairs in Tweet in G5:
[77] uk,#sugartax [68] sugar,drinks [68] less,sugar [67] #sugartax,working [67] important,research [67] working,people [67] people,getting [67] getting,less [67] bmj,uk [67] today's,bmj Top Word Pairs in Tweet in G6:
[131] #sugartax,#plastictax [128] sensibilità,premier [128] nel,2022 [128] 2022,grazie [127] matteosalvinimi,niente [127] niente,#sugartax [127] impegno,lega [127] grazie,impegno [127] premier,governo [127] alle,sensibilità Top Word Pairs in Tweet in G7:
[62] pro,health [41] health,taxes [38] health,financing [36] sugar,sweetened [32] webinar,series [31] nigeria,pro [31] policy,dialogue [30] sector,stakeholders [30] key,sector [30] series,nigeria Top Word Pairs in Tweet in G8:
[94] food,poverty [92] more,expensive [92] sugar,salt [89] sugary,salty [88] salt,taxes [88] foods,more [88] poverty,poor [88] don,solve [88] salty,foods [88] diet,making Top Word Pairs in Tweet in G9:
[45] implemented,more [45] taxes,sugar [45] beverages,implemented [45] #ssb,taxes [45] 73,countries [45] sugar,sweetened [45] more,73 [45] countries,#ssb [45] sweetened,beverages [44] ncdalliance,taxes Top Word Pairs in Tweet in G10:
[11] costs,australian [10] year,lost [10] australian,taxpayers [10] cola,alone [10] coca,cola [10] alone,costs [10] billion,dollars [10] one,billion [10] dollars,each [10] taxpayers,over Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Tweeters in Entire Graph:
Top Tweeters in G1:
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Top Tweeters in G10: