The graph represents a network of 48 Twitter users whose tweets in the requested range contained "pawcon", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 12 April 2019 at 14:34 UTC.
The requested start date was Friday, 12 April 2019 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 13-day, 11-hour, 2-minute period from Friday, 29 March 2019 at 09:01 UTC to Thursday, 11 April 2019 at 20:03 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 : 48
Unique Edges : 59
Edges With Duplicates : 41
Total Edges : 100
Number of Edge Types : 3
Mentions : 61
Tweet : 32
Replies to : 7
Self-Loops : 32
Reciprocated Vertex Pair Ratio : 0.0338983050847458
Reciprocated Edge Ratio : 0.0655737704918033
Connected Components : 8
Single-Vertex Connected Components : 2
Maximum Vertices in a Connected Component : 34
Maximum Edges in a Connected Component : 86
Maximum Geodesic Distance (Diameter) : 6
Average Geodesic Distance : 2.655462
Graph Density : 0.0270390070921986
Modularity : 0.45035
NodeXL Version : 1.0.1.410
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[35] predictive,analytics [24] analytics,world [17] dr,data [16] data,show [15] #doctordatashow,#machinelearning [12] few,questions [12] #pawcon,#machinelearning [11] deep,learning [10] anticipation,upcoming [10] upcoming,conference Top Word Pairs in Tweet in G1:
[17] dr,data [16] predictive,analytics [16] data,show [15] #doctordatashow,#machinelearning [11] analytics,world [6] eric,siegel [5] anticipation,upcoming [5] upcoming,conference [5] conference,presentation [5] presentation,predictive Top Word Pairs in Tweet in G2:
[7] join,session [6] predictive,analytics [6] analytics,world [4] fingerprinting,trains [4] trains,rail [4] rail,vibration [4] vibration,deep [4] deep,learning [4] learning,join [4] session,andreas Top Word Pairs in Tweet in G3:
[10] predictive,analytics [8] few,questions [5] analytics,world [5] world,healthcare [4] jamet123,answers [4] answers,few [4] questions,incorporating [4] incorporating,#predictiveanalytics [4] #predictiveanalytics,business [4] business,#machinelearning Top Word Pairs in Tweet in G4:
[4] pawcon,example [4] example,recent [4] recent,work [4] work,journalists [4] journalists,nujournalism [4] nujournalism,storybench [4] storybench,#datascience [4] #datascience,#rstats [4] #rstats,#tidytuesday [3] datasartoriasf,pawcon Top Word Pairs in Tweet in G6:
[2] video,streak [2] streak,lately [2] lately,took [2] took,few [2] few,photos [2] photos,past [2] past,few [2] few,weeks [2] weeks,pawcon Top Word Pairs in Tweet in G8:
[7] deep,learning [3] june,16 [3] 16,20 [2] 20,vegas [2] vegas,#pawcon [2] learning,world [2] world,june [2] learning,mobile [2] mobile,come [2] come,learn Top Word Pairs in Tweet in G10:
[2] predictive,analytics [2] #pawcon,#machinelearning Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Mentioned in Entire Graph:
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Top Tweeters in Entire Graph:
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Top Tweeters in G10: