The graph represents a network of 4,349 Twitter users whose recent tweets contained "#NeurIPS2019", 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 Tuesday, 10 December 2019 at 04:17 UTC.
The tweets in the network were tweeted over the 9-day, 3-hour, 2-minute period from Sunday, 01 December 2019 at 00:42 UTC to Tuesday, 10 December 2019 at 03:45 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 : 4349
Unique Edges : 10916
Edges With Duplicates : 3624
Total Edges : 14540
Self-Loops : 1360
Reciprocated Vertex Pair Ratio : 0.0236844448401745
Reciprocated Edge Ratio : 0.0462729407671566
Connected Components : 272
Single-Vertex Connected Components : 188
Maximum Vertices in a Connected Component : 3885
Maximum Edges in a Connected Component : 13910
Maximum Geodesic Distance (Diameter) : 10
Average Geodesic Distance : 3.897979
Graph Density : 0.000608002812561675
Modularity : 0.559626
NodeXL Version : 1.0.1.422
Data Import : The graph represents a network of 4,349 Twitter users whose recent tweets contained "#NeurIPS2019", 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 Tuesday, 10 December 2019 at 04:17 UTC.
The tweets in the network were tweeted over the 9-day, 3-hour, 2-minute period from Sunday, 01 December 2019 at 00:42 UTC to Tuesday, 10 December 2019 at 03:45 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 : #NeurIPS2019
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 : Followers
Vertex Alpha : Followers
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[392] check,out [373] next,week [336] full,paper [327] poster,#neurips2019 [323] catch,poster [319] first,full [319] paper,pytorch [319] pytorch,3 [319] 3,years [319] years,development Top Word Pairs in Tweet in G1:
[210] #neurips2019,attendees [199] whova,event [199] event,app [198] attendees,new [198] new,discussion [198] started,join [198] join,conversation [198] conversation,whova [104] #wiml2019,#neurips2019 [97] check,out Top Word Pairs in Tweet in G2:
[152] normalizing,flows [151] gpapamak,eric_nalisnick [151] eric_nalisnick,deepspiker [151] deepspiker,balajiln [151] balajiln,shakir_za [144] looking,something [144] something,read [144] read,flight [144] flight,#neurips2019 [144] #neurips2019,read Top Word Pairs in Tweet in G3:
[265] first,full [265] full,paper [265] paper,pytorch [265] pytorch,3 [265] 3,years [265] years,development [265] development,describes [265] describes,goals [265] goals,design [265] design,principles Top Word Pairs in Tweet in G4:
[170] ml,model [101] riakall,#neurips2019 [85] model,doing [85] doing,good [85] good,wrong [85] wrong,question [85] question,asking [85] asking,need [85] need,ask [85] ask,ml Top Word Pairs in Tweet in G5:
[65] deep,learning [59] #neurips2019,tutorial [50] presented,#neurips2019 [48] know,relu [48] relu,nn's [48] nn's,output [48] output,score [48] score,decomposed [48] decomposed,exactly [48] exactly,gradient Top Word Pairs in Tweet in G6:
[118] medical,imaging [111] #neurips2019,paper [109] transfer,learning [109] learning,medical [108] imaging,affect [108] affect,performance [108] performance,representations [108] representations,convergence [108] surprising,conclusions [100] learn,more Top Word Pairs in Tweet in G7:
[16] looking,forward [12] vancouver,#neurips2019 [9] neurips,2019 [8] #neurips2019,next [8] deep,learning [8] machine,learning [7] learn,more [7] next,week [7] #neurips2019,conference [6] first,time Top Word Pairs in Tweet in G8:
[51] machine,learning [44] week's,excitement [44] excitement,adventure [44] adventure,machine [44] learning,#neurips2019 [44] #neurips2019,talks [44] talks,slides [44] slides,live [44] live,being [44] being,posted Top Word Pairs in Tweet in G9:
[95] ibm,research [63] neurips,2019 [61] #ai,#neurips2019 [56] check,out [45] learn,more [42] research,#ai [42] more,work [42] work,scientists [41] dec,8 [35] #ibmresearch,#neurips2019 Top Word Pairs in Tweet in G10:
[15] happy,chat [14] speaking,#neurips2019 [14] #neurips2019,retrospectives [14] retrospectives,workshop [14] workshop,talk [14] talk,title [14] title,active [14] active,symbols [14] symbols,analogy [14] analogy,making 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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Top Tweeters in G10: