The graph represents a network of 5,022 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 Wednesday, 27 November 2019 at 03:58 UTC.
The requested start date was Monday, 25 November 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 3-day, 6-hour, 9-minute period from Thursday, 21 November 2019 at 18:51 UTC to Monday, 25 November 2019 at 01:00 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 : 5022
Unique Edges : 6039
Edges With Duplicates : 1111
Total Edges : 7150
Number of Edge Types : 3
Tweet : 1103
Mentions : 5889
Replies to : 158
Self-Loops : 1103
Reciprocated Vertex Pair Ratio : 0.0111960191931758
Reciprocated Edge Ratio : 0.0221441124780316
Connected Components : 804
Single-Vertex Connected Components : 400
Maximum Vertices in a Connected Component : 2893
Maximum Edges in a Connected Component : 4617
Maximum Geodesic Distance (Diameter) : 16
Average Geodesic Distance : 5.90893
Graph Density : 0.000225655195213159
Modularity : 0.788347
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 5,022 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 Wednesday, 27 November 2019 at 03:58 UTC.
The requested start date was Monday, 25 November 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 3-day, 6-hour, 9-minute period from Thursday, 21 November 2019 at 18:51 UTC to Monday, 25 November 2019 at 01:00 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:
[407] october,39 [407] 39,people [407] people,found [407] found,dead [407] dead,lorry [407] lorry,outpouring [407] outpouring,national [407] national,shock [407] shock,grief [407] grief,november Top Word Pairs in Tweet in G1:
[164] choses,simples [164] simples,faire [164] faire,l'#immigration [164] l'#immigration,regardez [164] regardez,l'australie [164] l'australie,utilise [164] utilise,sa [164] sa,marine [164] marine,intercepter [163] racinesdavelyon,choses Top Word Pairs in Tweet in G2:
[404] october,39 [404] 39,people [404] people,found [404] found,dead [404] dead,lorry [404] lorry,outpouring [404] outpouring,national [404] national,shock [404] shock,grief [404] grief,november Top Word Pairs in Tweet in G3:
[11] read,more [10] youtube,video [10] video,over [10] over,5000 [10] 5000,views [10] views,days [10] days,check [10] check,#americafirst [10] #americafirst,#immigration [10] #immigration,#college Top Word Pairs in Tweet in G4:
[263] link,#smartdissent [255] more,children [255] children,stolen [255] stolen,parents [255] parents,border [255] border,knew [255] knew,link [220] smartdissent,more [220] #smartdissent,#families [35] #smartdissent,#familiesbelongtogether Top Word Pairs in Tweet in G5:
[15] #immigration,myvisahelp [7] myvisahelp,ailanational [6] vote,trump [5] myvisahelp,natimmforum [5] #djt,approve [5] approve,message [5] message,dear [5] dear,potus [5] potus,realdonaldtrump [5] realdonaldtrump,video Top Word Pairs in Tweet in G6:
[132] striking,contrast [132] contrast,between [132] between,stuart_mcdonald [132] stuart_mcdonald,patient [132] patient,detailed [132] detailed,explanation [132] explanation,benefits [132] benefits,thesnp [132] thesnp,#immigration [132] #immigration,policy Top Word Pairs in Tweet in G7:
[58] brexit,presents [58] presents,golden [58] golden,opportunity [58] opportunity,establish [58] establish,responsible [58] responsible,well [58] well,managed [58] managed,immigration [58] immigration,system [58] system,piece Top Word Pairs in Tweet in G8:
[56] apple,employed [33] trump,administration [33] administration,ordered [33] ordered,rangers [33] rangers,national [33] national,parks [33] parks,around [33] around,country [33] country,travel [33] travel,mexico Top Word Pairs in Tweet in G9:
[101] #psa,#nrc [101] #nrc,#rt [101] #rt,something [101] something,really [101] really,disturbing [101] disturbing,happened [101] happened,today [101] today,landed [101] landed,#india [101] #india,coming Top Word Pairs in Tweet in G10:
[24] #alien,#immigration [24] don,see [22] see,appsame [21] #immigration,#video [18] dems,don [15] #video,dems [13] #illegal,#alien [11] illegal,#alien [11] jimeastridge1,usacsmret [10] appsame,diamondandsilk Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G5:
Top Replied-To in G7:
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: