The graph represents a network of 4,955 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, 17 February 2020 at 04:22 UTC.
The requested start date was Monday, 17 February 2020 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, 2-hour, 21-minute period from Thursday, 13 February 2020 at 09:01 UTC to Saturday, 15 February 2020 at 11:23 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 : 4955
Unique Edges : 5378
Edges With Duplicates : 945
Total Edges : 6323
Number of Edge Types : 4
Tweet : 915
MentionsInRetweet : 4499
Mentions : 786
Replies to : 123
Self-Loops : 915
Reciprocated Vertex Pair Ratio : 0.0105598724845587
Reciprocated Edge Ratio : 0.0208990536277603
Connected Components : 766
Single-Vertex Connected Components : 415
Maximum Vertices in a Connected Component : 2970
Maximum Edges in a Connected Component : 3831
Maximum Geodesic Distance (Diameter) : 20
Average Geodesic Distance : 4.86571
Graph Density : 0.000206623438153719
Modularity : 0.768026
NodeXL Version : 1.0.1.423
Data Import : The graph represents a network of 4,955 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, 17 February 2020 at 04:22 UTC.
The requested start date was Monday, 17 February 2020 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, 2-hour, 21-minute period from Thursday, 13 February 2020 at 09:01 UTC to Saturday, 15 February 2020 at 11:23 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 : 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:
[1461] speaking,#citizenship [1461] #citizenship,imagine [1461] imagine,#democratmob [1461] #democratmob,respected [1461] respected,protected [1461] protected,imagine [1460] realjameswoods,speaking [171] stephen,miller [140] third,reich [123] white,supremacist Top Word Pairs in Tweet in G1:
[1448] speaking,#citizenship [1448] #citizenship,imagine [1448] imagine,#democratmob [1448] #democratmob,respected [1448] respected,protected [1448] protected,imagine [1447] realjameswoods,speaking [2] #trump,vinegar [2] vinegar,#hillary [2] #hillary,arsenic Top Word Pairs in Tweet in G2:
[161] stephen,miller [134] third,reich [115] white,supremacist [100] millercrime,stephen [93] one,critical [93] critical,reasons [93] reasons,third [93] reich,cover [93] cover,#concentrationcamps [93] #concentrationcamps,years Top Word Pairs in Tweet in G3:
[16] search,law [16] law,firms [16] #divorce,#personalinjury [16] #personalinjury,#wills [16] #wills,#realestate [16] #realestate,#dui [16] #dui,#immigration [16] #immigration,#commerciallaw [16] #commerciallaw,more [13] #canadapr,#expressentry Top Word Pairs in Tweet in G4:
[15] dvillella,realdonaldtrump [15] realdonaldtrump,bad [15] bad,racist [15] racist,people [15] people,realdonaldtrump [15] realdonaldtrump,whitehouse [15] whitehouse,share [14] soloyochapin,dvillella [14] share,#immigrat [8] michellemalkin,look Top Word Pairs in Tweet in G5:
[49] recent,podcast [49] podcast,nytimes [49] nytimes,software [49] software,engineer [49] engineer,hampshire [49] hampshire,tells [49] tells,reporter [49] reporter,laid [48] ustechworkers,recent [41] #sb386,#hb1044 Top Word Pairs in Tweet in G6:
[30] morning,fwdus [30] fwdus,president [30] president,thetoddschulte [30] thetoddschulte,cnn [30] cnn,discussed [30] discussed,trump [30] trump,administration's [30] administration's,expanded [30] expanded,travel [30] travel,ban Top Word Pairs in Tweet in G7:
[20] #haveaheart,#immigration [19] reunited,278 [19] 278,days [19] days,apart [19] apart,first [19] first,time [19] time,fiance [19] fiance,met [19] met,daughter [19] daughter,#haveaheart Top Word Pairs in Tweet in G8:
[74] india,becoming [74] becoming,silicon [74] silicon,valley [74] valley,many [74] many,indians [74] indians,graduating [74] graduating,universities [74] universities,returning [74] returning,india [74] india,create Top Word Pairs in Tweet in G9:
[83] oh,wonderful [83] wonderful,#democratsaredestroyingamerica [83] #democratsaredestroyingamerica,horrendous [83] horrendous,#immigration [83] #immigration,laws [83] laws,seventy [83] seventy,five [83] five,percent [83] percent,illegal [82] gerisk,oh Top Word Pairs in Tweet in G10:
[25] #conservateurs,avons [25] avons,stratégie [25] stratégie,forte [25] forte,ns [25] ns,défendons [25] défendons,civilisation [25] civilisation,non [25] non,marché [24] racinesdavenir,#conservateurs [24] marché,indiv Top Replied-To in Entire Graph:
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Top Replied-To in G9:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Mentioned in G10:
Top Tweeters in Entire Graph:
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Top Tweeters in G10: