The graph represents a network of 2 039 Twitter users whose recent tweets contained "moody's brexit", 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 Wednesday, 21 October 2020 at 09:13 UTC.
The tweets in the network were tweeted over the 7-day, 10-hour, 13-minute period from Tuesday, 13 October 2020 at 22:03 UTC to Wednesday, 21 October 2020 at 08:17 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 : 2039
Unique Edges : 2219
Edges With Duplicates : 143
Total Edges : 2362
Number of Edge Types : 5
Tweet : 356
Retweet : 1718
MentionsInRetweet : 107
Mentions : 114
Replies to : 67
Self-Loops : 365
Reciprocated Vertex Pair Ratio : 0,00256673511293634
Reciprocated Edge Ratio : 0,00512032770097286
Connected Components : 301
Single-Vertex Connected Components : 206
Maximum Vertices in a Connected Component : 1414
Maximum Edges in a Connected Component : 1693
Maximum Geodesic Distance (Diameter) : 13
Average Geodesic Distance : 4,30475
Graph Density : 0,000469981580957396
Modularity : 0,797023
NodeXL Version : 1.0.1.441
Data Import : The graph represents a network of 2 039 Twitter users whose recent tweets contained "moody's brexit", 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 Wednesday, 21 October 2020 at 09:13 UTC.
The tweets in the network were tweeted over the 7-day, 10-hour, 13-minute period from Tuesday, 13 October 2020 at 22:03 UTC to Wednesday, 21 October 2020 at 08:17 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 : TwitterSearch
Graph Term : moody's brexit
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:
[685] moody's,downgrades [450] credit,rating [419] covid,19 [377] downgrades,uk [360] 19,brexit [359] uk,credit [352] hit,debt [351] debt,outlook [343] uk,covid [334] rating,downgraded Top Word Pairs in Tweet in G1:
[267] #breaking,moody's [267] moody's,downgrades [267] downgrades,#britain [267] #britain,debt [267] debt,ratings [267] ratings,aa3 [267] aa3,#brexit [267] #brexit,damage [4] credit,rating [3] moody,downgrades Top Word Pairs in Tweet in G2:
[236] moody's,downgrades [226] downgrades,uk [226] uk,covid [226] covid,19 [226] hit,debt [226] debt,outlook [194] 19,brexit [194] brexit,hit [39] lowered,rating [39] rating,aa3 Top Word Pairs in Tweet in G3:
[65] covid,19 [58] moody's,downgrades [55] downgrades,uk [52] 19,brexit [46] uk,covid [46] hit,debt [45] debt,outlook [44] brexit,hit [26] uk,credit [26] credit,rating Top Word Pairs in Tweet in G4:
[187] moody's,downrates [187] downrates,uk [187] uk,govt's [187] govt's,failure [187] failure,manage [187] manage,change [187] change,predictable [187] predictable,confidence [187] confidence,building [187] building,manner Top Word Pairs in Tweet in G5:
[161] moody's,citing [161] citing,weakening [159] united,kingdom [159] kingdom,sovereign [159] sovereign,debt [159] debt,rating [159] rating,lowered [159] lowered,moody's [159] weakening,economic [159] economic,fiscal Top Word Pairs in Tweet in G6:
[112] uk,credit [112] credit,rating [112] rating,downgraded [109] coronavirus,crisis [106] downgraded,notch [106] notch,moody [106] moody,coronavirus [106] crisis,worsens [106] worsens,brexit [106] brexit,prospects Top Word Pairs in Tweet in G7:
[87] downgraded,moody's [79] rating,downgraded [78] credit,rating [77] benefits,brexit [77] brexit,uk [77] uk,credit [77] moody's,growth [77] growth,concerns [13] moody's,downgrades [11] downgrades,uk Top Word Pairs in Tweet in G8:
[40] aa3,stable [37] stable,october [37] october,2020 [33] aa1,stable [33] stable,2014 [33] 2014,aa1 [33] aa1,negative [33] negative,june [33] june,24th [33] 24th,2016 Top Word Pairs in Tweet in G9:
[50] uk,credit [50] credit,rating [50] rating,downgraded [50] downgraded,moody's [50] moody's,growth [50] growth,concerns [50] concerns,ratings [50] ratings,agency [50] agency,cites [50] cites,weakening Top Word Pairs in Tweet in G10:
[64] rating,cut [34] cut,moody [34] moody,softer [34] softer,economic [34] economic,growth [34] growth,erosion [34] erosion,fiscal [34] fiscal,strength [34] strength,weakening [34] weakening,institutions Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G5:
Top Replied-To in G6:
Top Replied-To in G7:
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 G6:
Top Mentioned in G7:
Top Mentioned in G8:
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: