The graph represents a network of 10,578 Twitter users whose recent tweets contained "#Remain", 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 Thursday, 07 November 2019 at 11:28 UTC.
The tweets in the network were tweeted over the 4-day, 15-hour, 47-minute period from Saturday, 02 November 2019 at 18:51 UTC to Thursday, 07 November 2019 at 10:38 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 : 10578
Unique Edges : 30478
Edges With Duplicates : 10808
Total Edges : 41286
Self-Loops : 1717
Reciprocated Vertex Pair Ratio : 0.00767918088737201
Reciprocated Edge Ratio : 0.0152413209144793
Connected Components : 565
Single-Vertex Connected Components : 379
Maximum Vertices in a Connected Component : 9717
Maximum Edges in a Connected Component : 40380
Maximum Geodesic Distance (Diameter) : 12
Average Geodesic Distance : 3.831548
Graph Density : 0.000295557416658001
Modularity : 0.421309
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 10,578 Twitter users whose recent tweets contained "#Remain", 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 Thursday, 07 November 2019 at 11:28 UTC.
The tweets in the network were tweeted over the 4-day, 15-hour, 47-minute period from Saturday, 02 November 2019 at 18:51 UTC to Thursday, 07 November 2019 at 10:38 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 : #Remain
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:
[1314] #remain,candidate [1019] #remain,party [1016] don,t [904] nhs,schools [886] single,#remain [733] plaid,cymru [711] #remain,bonus [697] party,#remain [681] 60,seats [665] cymru,greens Top Word Pairs in Tweet in G1:
[222] #stopbrexit,#remain [221] #remain,party [211] don,t [200] vote,#remain [186] northern,ireland [137] tactical,voting [132] #remain,candidate [130] pro,#remain [125] lib,dem [109] #remain,candidates Top Word Pairs in Tweet in G2:
[562] nhs,schools [469] #remain,party [401] back,#remain [359] single,#remain [358] #remain,joswinson [295] #remain,candidate [277] johnson,s [263] together,#stopbrexit [262] utter,waste [261] #stopbrexit,back Top Word Pairs in Tweet in G3:
[403] #remain,bonus [399] bonus,over [266] 5,years [260] 50bn,#remain [259] institute,fiscal [259] fiscal,studies [258] theifs,institute [258] studies,assumptions [258] assumptions,figures [258] figures,underpinning Top Word Pairs in Tweet in G4:
[248] #remain,candidate [115] chance,winning [95] seats,#remain [95] candidate,chance [95] seats,uklabour [95] uklabour,tories [94] over,50 [94] 50,seats [94] candidate,#remain [94] winning,seats Top Word Pairs in Tweet in G5:
[371] #remain,candidate [343] single,#remain [336] 60,seats [332] plaid,cymru [331] cymru,greens [327] heidiallen75,unitetoremain [325] progressive,#remainalliance [325] #remainalliance,confirmed [325] confirmed,60 [325] seats,49 Top Word Pairs in Tweet in G6:
[277] thank,x [272] lib,dem [270] labour,lib [270] dem,tory [269] tory,party [269] party,#remain [269] #remain,m [269] m,trying [269] trying,best [269] best,millions Top Word Pairs in Tweet in G7:
[161] vote,tactically [159] stop,tories [155] 'you,vote [155] tactically,change [155] change,actual [155] actual,views [155] views,one [155] one,cross [155] cross,one [155] one,ballot Top Word Pairs in Tweet in G8:
[37] #brexit,#remain [15] #remain,#stopbrexit [15] #leave,#remain [13] don,t [11] voted,#remain [11] vote,#remain [11] #stopbrexit,#remain [10] #remain,#brexit [9] #remain,vote [9] #remainalliance,#remain Top Word Pairs in Tweet in G9:
[85] 17,4m [84] here's,poll [84] poll,vote [84] vote,12 [84] 12,12 [84] 12,19 [84] 19,#leave [84] #leave,#brexitparty [84] #brexitparty,#dup [84] #dup,people Top Word Pairs in Tweet in G10:
[260] nick,nick [260] nick,air [260] air,women [260] women,keep [260] keep,knickers [260] knickers,avoid [260] avoid,being [260] being,raped [260] raped,nick [260] nick,announced 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:
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Top Tweeters in G5:
Top Tweeters in G6:
Top Tweeters in G7:
Top Tweeters in G8:
Top Tweeters in G9:
Top Tweeters in G10: