The graph represents a network of 2,879 Twitter users whose recent tweets contained "conversation_id:1725547907430900200", or who were replied to, mentioned, retweeted or quoted in those tweets, taken from a data set limited to a maximum of 20,000 tweets, tweeted between 17/11/2023 16:00:00 and 19/12/2023 12:10:41. The network was obtained from Twitter on Tuesday, 19 December 2023 at 12:58 UTC.
The tweets in the network were tweeted over the 200-day, 22-hour, 45-minute period from Thursday, 01 June 2023 at 14:12 UTC to Tuesday, 19 December 2023 at 12:58 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 Spiral layout algorithm.
Vertices : 2879
Unique Edges : 3696
Edges With Duplicates : 1720
Total Edges : 5416
Number of Edge Types : 6
Replies to : 3373
MentionsInReplyTo : 2003
MentionsInQuoteReply : 21
Quote : 13
Tweet : 5
Mentions : 1
Self-Loops : 26
Reciprocated Vertex Pair Ratio : 0.0243362831858407
Reciprocated Edge Ratio : 0.0475161987041037
Connected Components : 1
Single-Vertex Connected Components : 0
Maximum Vertices in a Connected Component : 2879
Maximum Edges in a Connected Component : 5416
Maximum Geodesic Distance (Diameter) : 5
Average Geodesic Distance : 2.095204
Graph Density : 0.000502910897030352
Modularity : 0.377232
NodeXL Version : 1.0.1.527
Data Import : The graph represents a network of 2,879 Twitter users whose recent tweets contained "conversation_id:1725547907430900200", or who were replied to, mentioned, retweeted or quoted in those tweets, taken from a data set limited to a maximum of 20,000 tweets, tweeted between 17/11/2023 16:00:00 and 19/12/2023 12:10:41. The network was obtained from Twitter on Tuesday, 19 December 2023 at 12:58 UTC.
The tweets in the network were tweeted over the 200-day, 22-hour, 45-minute period from Thursday, 01 June 2023 at 14:12 UTC to Tuesday, 19 December 2023 at 12:58 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 Spiral layout algorithm.
Graph Source : TwitterSearch3
Graph Term : conversation_id:1725547907430900200
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:
[163] female,officer [138] cdoggthfc,crimeldn [138] crimeldn,police [132] crimeldn,prime_time_100 [132] crimeldn,female [113] kowalski49870,crimeldn [104] diegofuego71,crimeldn [88] freedomcat20,crimeldn [84] police,officer [82] police,officers Top Word Pairs in Tweet in G1:
[117] female,officer [115] crimeldn,female [100] crimeldn,police [53] police,officers [51] police,officer [38] female,police [35] police,force [32] crimeldn,pathetic [31] crimeldn,woman [27] crimeldn,embarrassing Top Word Pairs in Tweet in G2:
[61] crimeldn,metpoliceuk [7] female,officer [4] hbghoopster,crimeldn [4] crimeldn,well [4] fit,purpose [4] police,officer [3] markmercafc,crimeldn [3] more,training [3] metpoliceuk,female [3] crimeldn,mayoroflondon Top Word Pairs in Tweet in G3:
[128] cdoggthfc,crimeldn [16] crimeldn,police [7] lack,respect [6] female,officer [6] police,officer [5] crimeldn,women [5] help,police [4] mrtharb,crimeldn [4] horysmokes,crimeldn [4] crimeldn,respect Top Word Pairs in Tweet in G4:
[94] diegofuego71,crimeldn [10] duke0flancast3r,diegofuego71 [7] truthhurts101uk,crimeldn [6] crimeldn,useless [5] female,officers [5] police,officers [4] logicalbase,diegofuego71 [4] terracheck,crimeldn [4] shemj14,duke0flancast3r [4] female,police Top Word Pairs in Tweet in G5:
[98] kowalski49870,crimeldn [16] panayiotou17,crimeldn [15] kowalski49870,panayiotou17 [12] bananatoastnut,crimeldn [10] female,officer [10] leesteane7,kowalski49870 [7] female,officers [7] police,officer [7] panayiotou17,kowalski49870 [6] janerowe,leesteane7 Top Word Pairs in Tweet in G6:
[132] crimeldn,prime_time_100 [88] freedomcat20,crimeldn [75] fortesmentum,crimeldn [62] ctalexander19,freedomcat20 [34] lyfchek_le57040,ctalexander19 [20] good,morning [20] torymediacracy,ctalexander19 [17] morning,sir [17] torymediacracy,freedomcat20 [14] visionittv3313,crimeldn Top Word Pairs in Tweet in G7:
[46] naomisky_15,crimeldn [15] dawsonsleftpeg,crimeldn [8] karazazun,crimeldn [4] pepper,spray [4] edga38656,naomisky_15 [3] equal,pay [3] male,officers [3] moonlicker5000,crimeldn [3] female,officers [3] kowalski49870,crimeldn Top Word Pairs in Tweet in G8:
[33] mpskingston,crimeldn [17] dsr_f11,crimeldn [5] crimeldn,invictaregina [5] female,officer [3] lesbian,nana [3] crimeldn,metcc [2] work,again [2] male,officer [2] far,better [2] crimeldn,people Top Word Pairs in Tweet in G9:
[40] darren8319,crimeldn [7] crimeldn,police [6] klyntarfx,crimeldn [5] darren8319,klyntarfx [4] naomisky_15,crimeldn [3] call,brutality [3] borryai,darren8319 [3] female,officer [2] service,record [2] lose,job Top Word Pairs in Tweet in G10:
[28] shahmoneym,crimeldn [5] darcybbc,crimeldn [3] water,cannons [3] supports,israel [2] crimeldn,well [2] uk,support [2] mcdonalds,supports [2] muslim,country [2] police,force [2] crimeldn,uk Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
Top Replied-To in G3:
Top Replied-To in G4:
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 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: