The graph represents a network of 901 Twitter users whose tweets in the requested range contained "#ImmigrationReform", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Saturday, 09 July 2022 at 16:17 UTC.
The requested start date was Saturday, 09 July 2022 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 7,500.
The tweets in the network were tweeted over the 12-day, 22-hour, 27-minute period from Saturday, 25 June 2022 at 00:12 UTC to Thursday, 07 July 2022 at 22:39 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 : 901
Unique Edges : 700
Edges With Duplicates : 1550
Total Edges : 2250
Number of Edge Types : 5
Retweet : 617
MentionsInRetweet : 1053
Tweet : 199
Mentions : 258
Replies to : 123
Self-Loops : 219
Reciprocated Vertex Pair Ratio : 0.00265721877767936
Reciprocated Edge Ratio : 0.00530035335689046
Connected Components : 160
Single-Vertex Connected Components : 87
Maximum Vertices in a Connected Component : 510
Maximum Edges in a Connected Component : 1722
Maximum Geodesic Distance (Diameter) : 16
Average Geodesic Distance : 6.05287
Graph Density : 0.00139597977555802
Modularity : 0.487309
NodeXL Version : 1.0.1.449
Data Import : The graph represents a network of 901 Twitter users whose tweets in the requested range contained "#ImmigrationReform", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Saturday, 09 July 2022 at 16:17 UTC.
The requested start date was Saturday, 09 July 2022 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 7,500.
The tweets in the network were tweeted over the 12-day, 22-hour, 27-minute period from Saturday, 25 June 2022 at 00:12 UTC to Thursday, 07 July 2022 at 22:39 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 : #ImmigrationReform
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:
[129] united,states [124] path,citizenship [121] polls_unbiased,united [81] immigrants,living [80] states,deport [80] deport,immigrants [80] living,illegally [80] illegally,offer [80] offer,path [80] citizenship,follow Top Word Pairs in Tweet in G1:
[72] scoop,whitehouse [72] whitehouse,considering [72] considering,eo [72] eo,#immigration [72] #immigration,senate [72] senate,leadership [72] leadership,asked [72] asked,wh [72] wh,stall [72] stall,dems Top Word Pairs in Tweet in G2:
[8] san,antonio [7] #immigration,#immigrationreform [7] #immigrationattorney,#immigration [7] #immigration,#immigrationlaw [6] #immigrationlaw,#immigrationreform [5] found,dead [4] #immigrationreform,#texas [4] #immigrationreform,#immigrationservices [3] migrants,found [3] #immigrationreform,needed Top Word Pairs in Tweet in G3:
[122] united,states [122] path,citizenship [120] polls_unbiased,united [79] states,deport [79] deport,immigrants [79] immigrants,living [79] living,illegally [79] illegally,offer [79] offer,path [79] citizenship,follow Top Word Pairs in Tweet in G4:
[23] nigerian,immigrant [23] immigrant,terrorist [23] terrorist,need [23] need,deported [23] deported,immediately [23] immediately,anti [23] anti,american [23] american,hatred [23] hatred,threatening [22] adosempowering,nigerian Top Word Pairs in Tweet in G5:
[63] foreign,national [63] national,spouses [49] suffering,cruel [41] spouses,suffering [31] johnewrightjr1,repgregsteube [30] miamiherald,pbpost [29] support,rights [29] rights,citizens [27] floridians,foreign [25] cruel,inhumane Top Word Pairs in Tweet in G6:
[25] matthewjdowd,exec [25] exec,restaurant [25] restaurant,industry [25] industry,agriculture [25] agriculture,friends [25] friends,begging [25] begging,#immigrationreform [24] bidenwonthnkgod,matthewjdowd [6] title,42 [6] pass,#immigrationreform Top Word Pairs in Tweet in G8:
[24] republicans,help [24] help,democrats [24] democrats,create [24] create,#immigrationreform [24] #immigrationreform,republicans [24] republicans,solutions [23] solutions,problems [23] problems,republicans [23] republicans,entire [23] entire,campaign Top Word Pairs in Tweet in G9:
[8] need,#immigrationreform [4] #immigrationreform,potus [4] potus,lm [3] potus,vp [3] newshour,thestephsy [3] thestephsy,potus [3] dreamers2gether,need [2] #daca,#immigrationreform [2] time,#immigrationreform [2] #immigrationreform,ch Top Word Pairs in Tweet in G10:
[34] today,grieve [34] grieve,another [34] another,preventable [34] preventable,tragedy [34] tragedy,51 [34] 51,lives [34] lives,lost [34] lost,#tx23 [34] #tx23,epicenter [34] epicenter,ineffective Top Replied-To in Entire Graph:
Top Replied-To in G4:
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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:
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Top Tweeters in G7:
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Top Tweeters in G9:
Top Tweeters in G10: