The graph represents a network of 6,322 Twitter users whose recent tweets contained "#ABLeg", 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 Monday, 28 October 2019 at 17:02 UTC.
The tweets in the network were tweeted over the 1-day, 22-hour, 37-minute period from Saturday, 26 October 2019 at 16:45 UTC to Monday, 28 October 2019 at 15:23 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 : 6322
Unique Edges : 18048
Edges With Duplicates : 6178
Total Edges : 24226
Self-Loops : 1670
Reciprocated Vertex Pair Ratio : 0.0057660626029654
Reciprocated Edge Ratio : 0.0114660114660115
Connected Components : 107
Single-Vertex Connected Components : 71
Maximum Vertices in a Connected Component : 6159
Maximum Edges in a Connected Component : 24011
Maximum Geodesic Distance (Diameter) : 10
Average Geodesic Distance : 3.63636
Graph Density : 0.000488872226126827
Modularity : 0.380647
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 6,322 Twitter users whose recent tweets contained "#ABLeg", 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 Monday, 28 October 2019 at 17:02 UTC.
The tweets in the network were tweeted over the 1-day, 22-hour, 37-minute period from Saturday, 26 October 2019 at 16:45 UTC to Monday, 28 October 2019 at 15:23 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 : #ABLeg
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:
[4029] #ableg,#abpoli [2367] #ableg,#cdnpoli [1729] #abpoli,#ableg [1327] #ableg,#abbudget [1166] #cdnpoli,#ableg [1120] jason,kenney [856] income,tax [807] oil,gas [805] #ableg,#abed [786] #abpoli,#cdnpoli Top Word Pairs in Tweet in G1:
[1452] #ableg,#abpoli [659] #ableg,#cdnpoli [625] #abpoli,#ableg [575] #ableg,#abbudget [553] #abed,#ableg [465] #ableg,#abed [374] jason,kenney [266] over,management [258] point,talk [258] talk,teachers Top Word Pairs in Tweet in G2:
[852] #ableg,#cdnpoli [844] #ableg,#abpoli [540] #abpoli,#ableg [373] #cdnpoli,#ableg [351] jason,kenney [297] #ableg,#kenneycuts [240] prayer,breakfast [219] school,system [207] alberta,public [205] public,school Top Word Pairs in Tweet in G3:
[332] #ableg,#abpoli [260] #ableg,#cdnpoli [182] #cdnpoli,#ableg [145] #abpoli,#ableg [144] #abpoli,#cdnpoli [128] cabinet,represent [124] #ableg,#abbudget [124] trudeau,inflame [124] inflame,separatism [124] separatism,more Top Word Pairs in Tweet in G4:
[246] #ableg,#cdnpoli [236] #ableg,#abpoli [169] post,secondary [142] budget,2019 [129] income,taxes [129] secondary,institutions [129] religious,schools [128] jason,kenney's [128] publicly,funded [122] jason,kenney Top Word Pairs in Tweet in G5:
[502] #ableg,#abpoli [305] oil,gas [251] tax,cuts [216] public,services [216] #abpoli,#canlab [211] husky,ceo [211] really,appreciate [211] appreciate,tax [210] services,infrastructure [209] ceo,really Top Word Pairs in Tweet in G6:
[197] #ableg,#abpoli [183] income,tax [160] income,taxes [159] corporate,tax [153] #ableg,#abbudget [151] more,income [150] confused,right [150] right,now [150] now,albertans [150] albertans,uproar Top Word Pairs in Tweet in G7:
[276] #cdnpoli,#ableg [239] alberta,1 [237] more,more [237] more,canadians [237] canadians,feeling [237] feeling,impatience [237] impatience,w [237] w,alberta [237] 1,economic [237] economic,basketcase Top Word Pairs in Tweet in G8:
[91] #ableg,#abpoli [88] pay,more [87] income,tax [86] carbon,tax [80] auto,insurance [80] personal,income [80] school,fees [79] pay,federal [77] hated,ndp [77] ndp,carbon Top Word Pairs in Tweet in G9:
[106] re,raising [102] 000,jobs [99] tax,credits [98] 20,000 [95] ve,lost [93] temporary,employment [93] employment,program [92] cut,youth [92] youth,minimum [92] minimum,wage Top Word Pairs in Tweet in G10:
[171] #ableg,#abpoli [112] #abpoli,#ableg [102] #abpoli,#abbudget [98] jason,kenney [87] lost,job [87] ll,take [85] don,t [83] job,world [83] world,phasing [83] phasing,out 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 G7:
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: