The graph represents a network of 4,981 Twitter users whose tweets in the requested range contained "#Immigration", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Monday, 02 December 2019 at 04:17 UTC.
The requested start date was Monday, 02 December 2019 at 01:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 2-day, 21-hour, 21-minute period from Thursday, 28 November 2019 at 16:03 UTC to Sunday, 01 December 2019 at 13:24 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 : 4981
Unique Edges : 5647
Edges With Duplicates : 737
Total Edges : 6384
Number of Edge Types : 3
Mentions : 5557
Replies to : 126
Tweet : 701
Self-Loops : 701
Reciprocated Vertex Pair Ratio : 0.00594353640416048
Reciprocated Edge Ratio : 0.0118168389955687
Connected Components : 597
Single-Vertex Connected Components : 307
Maximum Vertices in a Connected Component : 3565
Maximum Edges in a Connected Component : 4711
Maximum Geodesic Distance (Diameter) : 17
Average Geodesic Distance : 4.71709
Graph Density : 0.000218339731138971
Modularity : 0.807025
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 4,981 Twitter users whose tweets in the requested range contained "#Immigration", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Monday, 02 December 2019 at 04:17 UTC.
The requested start date was Monday, 02 December 2019 at 01:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 2-day, 21-hour, 21-minute period from Thursday, 28 November 2019 at 16:03 UTC to Sunday, 01 December 2019 at 13:24 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 : GraphServerTwitterSearch
Graph Term : #Immigration
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:
[754] urge,both [754] both,reconsider [754] reconsider,dangerous [754] dangerous,unlawful [754] unlawful,course [754] course,action [754] action,#agbarr [754] #agbarr,denounced [750] epochtimes,urge [731] denounced,#oregon Top Word Pairs in Tweet in G1:
[744] urge,both [744] both,reconsider [744] reconsider,dangerous [744] dangerous,unlawful [744] unlawful,course [744] course,action [744] action,#agbarr [744] #agbarr,denounced [740] epochtimes,urge [721] denounced,#oregon Top Word Pairs in Tweet in G2:
[421] lieu,relancer [421] relancer,démographie [421] démographie,nationale [421] nationale,ces [421] ces,fous [421] fous,veulent [421] veulent,vider [421] vider,afrique [421] afrique,sa [421] sa,population Top Word Pairs in Tweet in G3:
[9] #immigration,#brexit [8] #immigration,#canada [8] search,law [8] law,firms [8] #divorce,#personalinjury [8] #personalinjury,#wills [8] #wills,#realestate [8] #realestate,#dui [8] #dui,#immigration [8] #immigration,#commerciallaw Top Word Pairs in Tweet in G4:
[254] jean,paul [254] paul,#delevoye [254] #delevoye,fait [254] fait,trucider [254] trucider,chez [254] chez,#cnews [254] #cnews,par [254] par,politologue [254] politologue,guillaume [254] guillaume,bigot Top Word Pairs in Tweet in G5:
[203] nephew,ideas [203] ideas,immigration [203] immigration,force [203] force,century [203] century,ago [203] ago,family [203] family,wiped [203] wiped,stephen [202] millercrime,nephew [202] stephen,mil Top Word Pairs in Tweet in G6:
[157] sick,tired [157] tired,being [157] being,talked [157] talked,numbers [157] numbers,spreadsheet [157] spreadsheet,actually [146] actually,people [146] people,loved [144] inlimbobrexit,sick [144] loved,fam Top Word Pairs in Tweet in G7:
[92] #immigration,#asile [91] #plf2020,mission [91] mission,#immigration [91] #asile,ccastaner [91] ccastaner,vante [91] vante,soudain [91] soudain,ma [91] ma,#cohérence [91] #cohérence,bon [91] bon,prends Top Word Pairs in Tweet in G8:
[39] stabbing,raping [39] raping,self [39] self,detonating [39] detonating,child [39] child,abusing [39] abusing,types [39] types,housedemocrats [39] housedemocrats,senategop [38] #blog,#essay [38] termc1,stabbing Top Word Pairs in Tweet in G9:
[73] andrebercoff,n'avons [73] n'avons,d'argent [73] d'argent,dizaines [73] dizaines,milliers [73] milliers,d'#agriculteurs [73] d'#agriculteurs,crèvent [73] crèvent,#france [73] #france,mais [73] mais,par [72] gauchemafia,andrebercoff Top Word Pairs in Tweet in G10:
[119] open,borders [119] borders,lobbying [119] lobbying,group [119] group,partially [119] partially,funded [119] funded,billionaire [119] billionaire,george [119] george,#soros [119] #soros,need [119] need,abolish Top Replied-To in Entire Graph:
Top Replied-To in G2:
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 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:
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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:
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Top Tweeters in G9:
Top Tweeters in G10: