The graph represents a network of 180 Twitter users whose recent tweets contained "#bundesligarating", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 10,000 tweets. The network was obtained from Twitter on Friday, 22 May 2020 at 10:11 UTC.
The tweets in the network were tweeted over the 18-minute period from Friday, 22 May 2020 at 09:52 UTC to Friday, 22 May 2020 at 10:11 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.
Author Description
Vertices : 180
Unique Edges : 183
Edges With Duplicates : 10
Total Edges : 193
Number of Edge Types : 4
Replies to : 120
Mentions : 20
Tweet : 41
Retweet : 12
Self-Loops : 41
Reciprocated Vertex Pair Ratio : 0
Reciprocated Edge Ratio : 0
Connected Components : 37
Single-Vertex Connected Components : 34
Maximum Vertices in a Connected Component : 142
Maximum Edges in a Connected Component : 156
Maximum Geodesic Distance (Diameter) : 6
Average Geodesic Distance : 2.247451
Graph Density : 0.00459342023587834
Modularity : 0.417434
NodeXL Version : 1.0.1.433
Data Import : The graph represents a network of 180 Twitter users whose recent tweets contained "#bundesligarating", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 10,000 tweets. The network was obtained from Twitter on Friday, 22 May 2020 at 10:11 UTC.
The tweets in the network were tweeted over the 18-minute period from Friday, 22 May 2020 at 09:52 UTC to Friday, 22 May 2020 at 10:11 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 : #bundesligarating
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 : In-Degree
Top Domains
Top Word Pairs in Tweet in G2:
[186] rating,10 [121] bester,einkauf [121] spieler,saison [120] saison,rating [120] trainer,rating [95] 10,#bundesligarating [93] 10,saison [63] kopieren,verein [55] 10,10 [52] sancho,flop Top Word Pairs in Tweet in G3:
[61] rating,10 [34] bester,einkauf [34] einkauf,alphonsodavies [34] alphonsodavies,spieler [33] spieler,saison [32] trainer,rating [30] 10,10 [15] 10,saison [8] saison,rating [8] 10,#bundesligarating Top Word Pairs in Tweet in G4:
[6] rating,10 [3] nico,schulz [3] bester,einkauf [3] spieler,saison [3] sancho,flop [3] trainer,rating [3] saison,rating [3] dortmund,bester [3] schulz,überraschung [3] schulz,trainer Top Word Pairs in Tweet in G5:
[12] rating,10 [8] verein,bvb [7] bvb,bester [7] bester,einkauf [7] spieler,saison [7] saison,sancho [7] sancho,flop [6] schulz,trainer [6] trainer,rating [6] 10,saison Top Word Pairs in Tweet in G6:
Top Word Pairs in Tweet in G9:
[] kopieren,verein [] verein,rein [] rein,verein [] verein,fc [] fc,bayern [] bayern,bester [] bester,einkauf [] einkauf,pavard [] pavard,spieler [] spieler,saison Top Word Pairs in Tweet in G10:
[2] rating,10 Top Replied-To in Entire Graph:
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Top Mentioned in Entire Graph:
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Top Tweeters in Entire Graph:
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