The graph represents a network of 223 Twitter users whose recent tweets contained "#notmychancellor", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 18,000 tweets. The network was obtained from Twitter on Friday, 22 November 2019 at 12:04 UTC.
The tweets in the network were tweeted over the 6-day, 4-hour, 44-minute period from Friday, 15 November 2019 at 22:22 UTC to Friday, 22 November 2019 at 03:07 UTC.
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.
Vertices : 223
Unique Edges : 402
Edges With Duplicates : 179
Total Edges : 581
Number of Edge Types : 4
Mentions : 191
Retweet : 290
Tweet : 75
Replies to : 25
Self-Loops : 75
Reciprocated Vertex Pair Ratio : 0.0306122448979592
Reciprocated Edge Ratio : 0.0594059405940594
Connected Components : 28
Single-Vertex Connected Components : 22
Maximum Vertices in a Connected Component : 180
Maximum Edges in a Connected Component : 534
Maximum Geodesic Distance (Diameter) : 7
Average Geodesic Distance : 3.266775
Graph Density : 0.00816062699470771
Modularity : 0.434758
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 223 Twitter users whose recent tweets contained "#notmychancellor", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 18,000 tweets. The network was obtained from Twitter on Friday, 22 November 2019 at 12:04 UTC.
The tweets in the network were tweeted over the 6-day, 4-hour, 44-minute period from Friday, 15 November 2019 at 22:22 UTC to Friday, 22 November 2019 at 03:07 UTC.
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 : TwitterSearch
Graph Term : #notmychancellor
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 : Followers
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[147] prince,andrew [65] huddersfield,student [49] hashtag,#notmychancellor [49] #princeandrew,#notmychancellor [48] resign,university [42] step,down [41] university,huddersfield [41] using,hashtag [38] huddersfield,students [37] huddersfield,chancellor Top Word Pairs in Tweet in G1:
[35] step,down [29] prince,andrew [25] huddersfield,student [25] student,union [25] union,voted [25] voted,yesterday [25] yesterday,evening [25] evening,campaign [25] campaign,prince [25] andrew,step Top Word Pairs in Tweet in G2:
[19] prince,andrew [15] well,#notmychancellor [13] well,aged [13] aged,well [11] don,t [11] #princeandrew,#notmychancellor [10] t,want [7] #notmychancellor,reading [7] reading,article [7] article,made Top Word Pairs in Tweet in G3:
[36] prince,andrew [19] resign,university [18] motion,passed [18] passed,huddersfield [18] huddersfield,student [18] student,panel [18] panel,agreement [18] agreement,prince [18] andrew,lobbied [18] lobbied,resign Top Word Pairs in Tweet in G4:
[33] #princeandrew,#notmychancellor [20] huddersfielduni,huddersfieldsu [20] sex,trafficking [19] don,t [19] t,want [19] #princeandew,#notmychancellor [12] want,racist [12] racist,sex [12] trafficking,symperthiser [12] symperthiser,chancellor Top Word Pairs in Tweet in G5:
[6] prince,andrew [3] chancellor,#notmychancellor [2] huddersfield,uni [2] huddersfield,university [2] role,model [2] #notmychancellor,campaign [2] #princeandew,#jefferyepstein [2] fully,support Top Word Pairs in Tweet in G6:
[32] huddersfield,students [20] prince,andrew [18] resign,university [16] students,pushing [16] pushing,prince [16] andrew,resign [16] university,chancellor [16] chancellor,huddersfield [16] students,expressing [16] expressing,support Top Word Pairs in Tweet in G7:
[10] students,supporting [10] supporting,decision [10] decision,using [10] using,hashtag [10] hashtag,#notmychancellor Top Word Pairs in Tweet in G8:
[8] prince,andrew [7] andrew,stepping [7] stepping,university [7] university,huddersfield [7] huddersfield,chancellor [7] chancellor,wake [7] wake,epstein [7] epstein,interview [7] interview,comes [7] comes,students Top Word Pairs in Tweet in G9:
[8] huddersfield,student [8] student,launches [8] launches,#notmychancellor [8] #notmychancellor,campaign [8] campaign,oust [8] oust,prince [8] prince,andrew [8] andrew,honorary [8] honorary,role [8] role,university Top Word Pairs in Tweet in G10:
[9] prince,andrew [5] university,huddersfield [3] chancellor,university [2] chancellor,#notmychancellor [2] time,come [2] come,huddersfielduni [2] huddersfielduni,decide [2] decide,continued [2] continued,affiliation [2] affiliation,prince 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 G8:
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 G6:
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:
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Top Tweeters in G7:
Top Tweeters in G8:
Top Tweeters in G9:
Top Tweeters in G10: