The graph represents a network of 5,464 Twitter users whose recent tweets contained "Laundromat", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 5,000 tweets. The network was obtained from Twitter on Thursday, 26 September 2019 at 10:38 UTC.
The tweets in the network were tweeted over the 5-day, 6-hour, 3-minute period from Saturday, 21 September 2019 at 04:17 UTC to Thursday, 26 September 2019 at 10:21 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 : 5464
Unique Edges : 5880
Edges With Duplicates : 466
Total Edges : 6346
Number of Edge Types : 4
Tweet : 1637
Retweet : 2785
Mentions : 1251
Replies to : 673
Self-Loops : 1664
Reciprocated Vertex Pair Ratio : 0.0116637323943662
Reciprocated Edge Ratio : 0.0230585164237546
Connected Components : 1806
Single-Vertex Connected Components : 1216
Maximum Vertices in a Connected Component : 771
Maximum Edges in a Connected Component : 944
Maximum Geodesic Distance (Diameter) : 22
Average Geodesic Distance : 3.644181
Graph Density : 0.000154004216841153
Modularity : 0.785299
NodeXL Version : 1.0.1.419
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[773] laundromat,works [772] day,needed [772] needed,go [772] go,emergency [772] emergency,room [772] room,wanting [772] wanting,sit [772] sit,hours [772] hours,put [772] put,magic Top Word Pairs in Tweet in G1:
[63] meryl,streep [47] go,laundromat [32] laundromat,review [31] steven,soderbergh [29] review,meryl [26] going,laundromat [26] streep,cycle [26] cycle,spin [23] october,2019 [22] everything,coming Top Word Pairs in Tweet in G2:
[772] day,needed [772] needed,go [772] go,emergency [772] emergency,room [772] room,wanting [772] wanting,sit [772] sit,hours [772] hours,put [772] put,magic [772] magic,black Top Word Pairs in Tweet in G3:
[481] laundromat,shot [6] hoes,wishy [6] wishy,washy [6] washy,laundromat Top Word Pairs in Tweet in G4:
[102] panama,papers [101] art,laundromat [101] laundromat,wouldn [101] wouldn,expect [101] expect,words [101] words,eccentric [101] eccentric,slap [101] slap,happy [101] happy,apply [101] apply,story Top Word Pairs in Tweet in G5:
[68] move,obscure [68] launder,money [68] money,massive [68] massive,scale [49] #laundromat,laun [49] laun,dro [49] dro,mat [49] mat,noun [49] noun,interconnected [49] interconnected,system Top Word Pairs in Tweet in G6:
[136] laundromat,junk [134] junk,science [128] goldson,nerdywonka [128] nerdywonka,cowgirl_bebop [120] cowgirl_bebop,drphilgoff [120] drphilgoff,laundromat [120] science,such [120] such,amazing [120] amazing,turn [120] turn,phrase Top Word Pairs in Tweet in G7:
[65] marriage,story [65] two,popes [62] dolemite,name [59] king,marriage [57] see,first [57] first,films [57] films,coming [57] coming,soon [57] soon,tiff [57] tiff,bell Top Word Pairs in Tweet in G8:
[77] shadows,dirty [77] dirty,anyone [77] anyone,take [77] take,laundromat [77] laundromat,paige [77] paige,lewis [77] lewis,space [77] space,struck Top Word Pairs in Tweet in G9:
[7] money,laundromat [7] ru,ian [4] one,comes [4] comes,clean [4] clean,laundromat [4] laundromat,steven [4] steven,soderbergh [4] soderbergh,playful [4] playful,panama [4] panama,papers Top Word Pairs in Tweet in G10:
[6] trump,russian [6] russian,laundromat [5] laundromat,money [5] money,laundering [5] laundering,gambling [5] gambling,rings [5] rings,sex [5] sex,trafficking [5] trafficking,fraud [5] fraud,corruption Top Replied-To in Entire Graph:
Top Replied-To in G4:
Top Replied-To in G5:
Top Replied-To in G6:
Top Replied-To in G7:
Top Replied-To in G9:
Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
Top Mentioned in G4:
Top Mentioned in G5:
Top Mentioned in G6:
Top Mentioned in G7:
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: