The graph represents a network of 4,706 Twitter users whose recent tweets contained "#Immigration", 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 3/5/2023 5:00:36 PM. The network was obtained from Twitter on Monday, 06 March 2023 at 23:20 UTC.
The tweets in the network were tweeted over the 1283-day, 9-hour, 28-minute period from Friday, 30 August 2019 at 15:18 UTC to Monday, 06 March 2023 at 00:47 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 : 4706
Unique Edges : 2559
Edges With Duplicates : 8755
Total Edges : 11314
Number of Edge Types : 9
Retweet : 3565
MentionsInRetweet : 4546
Mentions : 644
Tweet : 1058
Replies to : 296
MentionsInReplyTo : 678
Quote : 260
MentionsInQuote : 248
MentionsInQuoteReply : 19
Self-Loops : 1306
Reciprocated Vertex Pair Ratio : 0.00991852639036486
Reciprocated Edge Ratio : 0.0196422307962119
Connected Components : 694
Single-Vertex Connected Components : 415
Maximum Vertices in a Connected Component : 2377
Maximum Edges in a Connected Component : 6681
Maximum Geodesic Distance (Diameter) : 20
Average Geodesic Distance : 4.045227
Graph Density : 0.000257522786159889
Modularity : 0.476466
NodeXL Version : 1.0.1.510
Data Import : The graph represents a network of 4,706 Twitter users whose recent tweets contained "#Immigration", 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 3/5/2023 5:00:36 PM. The network was obtained from Twitter on Monday, 06 March 2023 at 23:20 UTC.
The tweets in the network were tweeted over the 1283-day, 9-hour, 28-minute period from Friday, 30 August 2019 at 15:18 UTC to Monday, 06 March 2023 at 00:47 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 : #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:
[807] partout,#france [799] bonnes,sœurs [799] sœurs,catholiques [799] #nantes,partout [799] anglais,peut [799] #france,anglais [799] églises,agresse [799] agresse,bonnes [799] catholiques,#nantes [799] attaque,églises Top Word Pairs in Tweet in G1:
[613] #nantes,partout [613] partout,#france [613] églises,agresse [613] #france,anglais [613] sœurs,catholiques [613] attaque,églises [613] agresse,bonnes [613] bonnes,sœurs [613] catholiques,#nantes [613] anglais,peut Top Word Pairs in Tweet in G2:
[24] #personalinjury,#wills [24] #realestate,#dui [24] #divorce,#personalinjury [24] search,law [24] #wills,#realestate [24] #commerciallaw,more [24] #immigration,#commerciallaw [24] law,firms [24] #dui,#immigration [20] #canada,#immigration Top Word Pairs in Tweet in G3:
[255] ils,ont [255] ménage,#jo2024 [255] faire,ménage [255] veulent,stopper [255] l'#immigration,mais [255] besoin,faire [255] mais,ils [255] ont,besoin [255] #jo2024,donc [255] ils,essaient Top Word Pairs in Tweet in G4:
[56] #nucléaire,#immigration [51] ont,toujours [50] lesrepublicains,ont [50] maintenant,meilleur [50] #electorat,nicolassarkozy [50] toujours,trahi [50] trahi,leur [50] leur,#electorat [50] nicolassarkozy,maintenant [50] meilleur,allié Top Word Pairs in Tweet in G5:
[175] mal,être [175] commerces,français [175] ville,mal [175] paris,seine [175] denis,ville [175] être,française [175] saint,denis [175] plus,tous [175] n'y,existent [175] français,n'y Top Word Pairs in Tweet in G6:
[123] #cdnimm,#immigration [107] #immigration,#canada [83] #canada,#ircc [56] international,students [56] #ircc,#canadavisa [51] #canadavisa,#cicnews [49] seanfrasermp,ongoing [49] crisis,international [49] students,ndp [49] ndp,liberal Top Word Pairs in Tweet in G7:
[109] 49,secondes [109] profitez,partagez [109] #immigration,#oqtf [109] #oqtf,#islam [109] bonheur,profitez [109] #remigration,#immigration [109] secondes,bonheur [109] partagez,#remigration [108] fredx92,49 [30] bonnes,sœurs Top Word Pairs in Tweet in G8:
[40] high,skilled [34] ironical,life [34] life,legal [34] legal,high [34] #immigration,#visabulletin [34] immigrant,please [34] potus,ironical [34] please,justice [34] uscis,potus [34] skilled,immigrant Top Word Pairs in Tweet in G9:
[42] taken,over [42] come,number [42] uk,hotels [42] govt,sometimes [42] over,uk [42] number,migrant [42] hotels,taken [42] secret,well [42] uk,govt [42] sometimes,secret Top Word Pairs in Tweet in G10:
[17] proposed,fee [16] join,npnewamericans [16] green,cards [16] benefits,join [16] citizenship,#immigration [16] #uscis,proposed [16] cards,citizenship [16] fee,hikes [16] #immigration,benefits [16] hikes,green Top Replied-To in Entire Graph:
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: