The graph represents a network of 26,455 Twitter users whose recent tweets were included in a list (Tweet ID List) of 34344 tweet IDs, or who were replied to or mentioned in those tweets. 33614 out of 34344 tweets were collected. The network was obtained from Twitter on Friday, 08 April 2022 at 02:28 UTC.
The tweets in the network were tweeted over the 1821-day, 23-hour, 27-minute period from Monday, 10 April 2017 at 19:14 UTC to Wednesday, 06 April 2022 at 18:41 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 : 26464
Unique Edges : 31818
Edges With Duplicates : 14842
Total Edges : 46660
Number of Edge Types : 5
Mentions : 7344
Retweet : 22880
Tweet : 10511
MentionsInRetweet : 4725
Replies to : 1200
Self-Loops : 10656
Reciprocated Vertex Pair Ratio : 0.0175793297238023
Reciprocated Edge Ratio : 0.0345512712577875
Connected Components : 4936
Single-Vertex Connected Components : 3965
Maximum Vertices in a Connected Component : 18812
Maximum Edges in a Connected Component : 35252
Maximum Geodesic Distance (Diameter) : 18
Average Geodesic Distance : 5.255918
Graph Density : 4.24022365922514E-05
Modularity : 0.63083
NodeXL Version : 1.0.1.449
Data Import : The graph represents a network of 26,455 Twitter users whose recent tweets were included in a list (Tweet ID List) of 34344 tweet IDs, or who were replied to or mentioned in those tweets. 33614 out of 34344 tweets were collected. The network was obtained from Twitter on Friday, 08 April 2022 at 02:28 UTC.
The tweets in the network were tweeted over the 1821-day, 23-hour, 27-minute period from Monday, 10 April 2017 at 19:14 UTC to Wednesday, 06 April 2022 at 18:41 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 : TwitterIDList
Graph Term : Tweet ID List
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:
[18090] bruce,willis [6571] diagnosed,aphasia [6013] aphasia,aphasia [5581] diagnosis,symptom [4649] stroke,brain [4620] caused,stroke [4614] brain,tumor [4554] aphasia,isn [4551] willis,first [4547] ve,seen Top Word Pairs in Tweet in G1:
[4118] bruce,willis [4080] diagnosed,aphasia [4075] brain,tumor [4070] stroke,brain [4062] aphasia,aphasia [4054] diagnosis,symptom [4044] ve,seen [4043] caused,stroke [4042] willis,first [4042] first,person Top Word Pairs in Tweet in G2:
[3442] bruce,willis [1340] aphasia,diagnosis [464] willis,aphasia [359] bruce,willis' [338] diagnosed,aphasia [276] actor,aphasia [238] away,acting [195] stepping,away [185] razzies,rescind [184] rescind,bruce Top Word Pairs in Tweet in G3:
[1292] bruce,willis [1085] willis,aphasia [1085] quite,common [1082] few,days [1082] days,people [1082] people,learned [1082] learned,jada [1082] jada,autoimmune [1082] autoimmune,disease [1082] disease,bruce Top Word Pairs in Tweet in G4:
[354] speech,language [315] language,therapy [267] people,aphasia [246] main,treatment [243] treatment,#aphasia [234] bruce,willis [214] please,correct [152] gmb,drhilaryjones [146] main,intervention [146] quality,life Top Word Pairs in Tweet in G5:
[1894] cause,aphasia [1215] bruce,willis [1191] aphasia,aphasia [1188] diagnosis,symptom [948] aphasia,diagnosis [948] common,cause [946] highly,mri [946] mri,bruce [946] willis,brain [946] brain,reveal Top Word Pairs in Tweet in G6:
[779] bruce,willis [173] night,shyamalan [171] diagnosed,aphasia [171] big,brother [171] brother,bruce [170] love,respect [169] respect,big [169] willis,night [169] shyamalan,know [169] know,wonderful Top Word Pairs in Tweet in G7:
[661] reading,bruce [661] bruce,willis' [661] willis',last [661] last,few [661] few,years [661] years,made [661] made,sad [661] sad,dare [661] dare,hollywood [661] hollywood,perform Top Word Pairs in Tweet in G8:
[632] bruce,willis [376] aphasia,diagnosis [370] million,americans [353] willis,aphasia [351] life,aphasia [350] news,broke [350] broke,bruce [350] diagnosis,ve [350] ve,gotten [350] gotten,lot Top Word Pairs in Tweet in G9:
[572] aphasia,symptom [544] symptom,diagnosis [542] diagnosis,add [37] bruce,willis [32] many,people [24] know,going [24] going,inside [21] don,know [20] loved,one [19] ok,wrote Top Word Pairs in Tweet in G10:
[670] bruce,willis [384] aphasia,diagnosis [176] bruce,willis' [117] haley,joel [117] joel,osment [110] worst,performance [109] following,aphasia [81] diagnosed,aphasia [77] willis',aphasia [76] stepping,away Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Replied-To in G8:
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Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Mentioned in G10:
Top Tweeters in Entire Graph:
Top Tweeters in G1:
Top Tweeters in G2:
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Top Tweeters in G5:
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Top Tweeters in G9:
Top Tweeters in G10: