The graph represents a network of 8,817 Twitter users whose recent tweets contained "#NRF2020", 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, 14 January 2020 at 19:22 UTC.
The tweets in the network were tweeted over the 1-day, 13-hour, 19-minute period from Monday, 13 January 2020 at 05:26 UTC to Tuesday, 14 January 2020 at 18:45 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 : 8817
Unique Edges : 18152
Edges With Duplicates : 14731
Total Edges : 32883
Number of Edge Types : 5
Mentions : 6791
MentionsInRetweet : 17513
Retweet : 5104
Replies to : 618
Tweet : 2857
Self-Loops : 2921
Reciprocated Vertex Pair Ratio : 0.0190985107119885
Reciprocated Edge Ratio : 0.03748118658057
Connected Components : 629
Single-Vertex Connected Components : 465
Maximum Vertices in a Connected Component : 7881
Maximum Edges in a Connected Component : 31626
Maximum Geodesic Distance (Diameter) : 12
Average Geodesic Distance : 3.848105
Graph Density : 0.000264979054857521
Modularity : 0.478058
NodeXL Version : 1.0.1.423
Data Import : The graph represents a network of 8,817 Twitter users whose recent tweets contained "#NRF2020", 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, 14 January 2020 at 19:22 UTC.
The tweets in the network were tweeted over the 1-day, 13-hour, 19-minute period from Monday, 13 January 2020 at 05:26 UTC to Tuesday, 14 January 2020 at 18:45 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 : #NRF2020
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:
[604] future,retail [571] day,#nrf2020 [528] booth,4221 [515] learn,more [447] one,day [446] 38,billion [446] billion,products [446] products,one [427] #nrf2020,nrfbigshow [426] humans,machines Top Word Pairs in Tweet in G1:
[290] #nrf2020,nrfbigshow [168] co,founder [152] #nrf2020,keynote [148] matthew,shay [141] recode,co [140] #nrf2020,#retailsfuture [137] nrffoundation,helps [137] helps,students [137] students,make [137] make,connections Top Word Pairs in Tweet in G2:
[218] #nrf2020,#ai [158] #ux,#ui [158] #ui,#nrf2020 [148] mind,blown [148] blown,#ux [129] #iot,#5g [129] #5g,#innovation [126] #retailtech,#nrf2020 [120] #retail,#retailtech [111] #ces2020,#nrf2020 Top Word Pairs in Tweet in G3:
[330] much,smarter [218] grocery,store [217] using,facial [217] facial,recognition [217] recognition,payments [217] payments,grocery [217] store,china [217] china,#nrf2020 [202] future,retail [188] reality,ar Top Word Pairs in Tweet in G4:
[393] #echangeurusa,#nrf2020 [214] evankirstel,lesguer_lionel [174] jblefevre60,evankirstel [159] jbonnel,jblefevre60 [137] lesguer_lionel,fmomboisse [137] fmomboisse,enjoydigitall [129] #nrf2020,#ai [106] #retail,#retailtech [106] enjoydigitall,c_chenevoy [100] #retailtech,#nrf2020 Top Word Pairs in Tweet in G5:
[515] booth,4221 [209] sap,retail [203] #nrf2020,sap_retail [189] day,#nrf2020 [164] learn,more [130] sap_retail,booth [121] today,jan [115] retail,booth [115] #nrf2020,#consciousconsumerism [114] 4221,#nrf2020 Top Word Pairs in Tweet in G6:
[44] nrf,2020 [37] stop,booth [36] day,#nrf2020 [35] big,show [30] learn,more [25] giving,away [24] booth,#3663 [23] make,sure [23] #cdwgetsretail,#cdwsocial [22] customer,experience Top Word Pairs in Tweet in G7:
[416] 38,billion [416] billion,products [416] products,one [416] one,day [353] humans,machines [352] alibaba,sell [352] sell,38 [352] day,workforce [352] workforce,future [352] future,humans Top Word Pairs in Tweet in G8:
[102] booth,5637 [89] come,see [68] #nrf2020,booth [57] stop,booth [53] lexmark,booth [48] learn,more [43] day,#nrf2020 [42] today,#nrf2020 [36] ray,ban [35] #nrf2020,technology Top Word Pairs in Tweet in G9:
[55] booth,#5919 [40] #nrf2020,know [38] transforming,#liveenterprise [36] customer,experience [34] day,#nrf2020 [29] galaxy,xcover [29] xcover,pro [29] join,#nrf2020 [27] seamless,commerce [26] wipro,#nrf2020 Top Word Pairs in Tweet in G10:
[53] booth,#3663 [35] ready,#nrf2020 [34] #cdwgetsretail,#nrf2020 [33] stop,booth [33] #gpus,dominos [33] dominos,train [33] train,algorithm [33] algorithm,less [33] less,hour [33] hour,retrain Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Replied-To in G7:
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Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Mentioned in G10:
Top Tweeters in Entire Graph:
Top Tweeters in G1:
Top Tweeters in G2:
Top Tweeters in G3:
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Top Tweeters in G9:
Top Tweeters in G10: