The graph represents a network of 5,230 Twitter users whose tweets in the requested range contained "supplychain", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Saturday, 05 September 2020 at 20:19 UTC.
The requested start date was Saturday, 05 September 2020 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 7,500.
The tweets in the network were tweeted over the 4-day, 8-hour, 44-minute period from Monday, 31 August 2020 at 15:16 UTC to Saturday, 05 September 2020 at 00:00 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 : 5230
Unique Edges : 3712
Edges With Duplicates : 9149
Total Edges : 12861
Number of Edge Types : 5
Tweet : 3745
Retweet : 3003
MentionsInRetweet : 3961
Mentions : 2080
Replies to : 72
Self-Loops : 3822
Reciprocated Vertex Pair Ratio : 0.0385422629269223
Reciprocated Edge Ratio : 0.0742237736542348
Connected Components : 1411
Single-Vertex Connected Components : 932
Maximum Vertices in a Connected Component : 2377
Maximum Edges in a Connected Component : 6821
Maximum Geodesic Distance (Diameter) : 18
Average Geodesic Distance : 5.699992
Graph Density : 0.000199029752808923
Modularity : 0.438339
NodeXL Version : 1.0.1.439
Data Import : The graph represents a network of 5,230 Twitter users whose tweets in the requested range contained "supplychain", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Saturday, 05 September 2020 at 20:19 UTC.
The requested start date was Saturday, 05 September 2020 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 7,500.
The tweets in the network were tweeted over the 4-day, 8-hour, 44-minute period from Monday, 31 August 2020 at 15:16 UTC to Saturday, 05 September 2020 at 00:00 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 : GraphServerTwitterSearch
Graph Term : supplychain
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:
[961] supply,chain [884] link,bio [539] click,link [438] retail,stocking [421] stocking,associate [400] #supplychain,job [317] harbor,freight [317] freight,tools [282] #supplychain,#logistics [262] see,latest Top Word Pairs in Tweet in G1:
[771] link,bio [474] click,link [388] retail,stocking [372] stocking,associate [343] #supplychain,job [281] harbor,freight [281] freight,tools [228] bio,apply [226] see,latest [200] supply,chain Top Word Pairs in Tweet in G2:
[81] supply,chain [35] learn,more [30] semiconductor,manufacturing [30] manufacturing,equipment [30] equipment,maker [30] maker,cohu [30] cohu,decided [30] decided,move [30] move,single [30] single,#cloud Top Word Pairs in Tweet in G3:
[156] supply,chain [67] #supplychain,#logistics [49] #ai,#machinelearning [48] #smart,pivoting [48] pivoting,sorter [48] sorter,mt [48] mt,jblefevre60 [48] jblefevre60,#ai [48] #machinelearning,#robotics [48] #robotics,#mi Top Word Pairs in Tweet in G4:
[137] supply,chain [58] business,strategy [56] chief,procurement [56] procurement,officers [56] officers,need [56] need,align [56] align,digital [56] digital,strategy [56] strategy,organization's [56] organization's,overall Top Word Pairs in Tweet in G5:
[139] need,#executive [139] #executive,#supplychain [139] #supplychain,#recruiter [139] #recruiter,dm [139] dm,codeofvets [139] codeofvets,veteran [139] veteran,needs [139] needs,assistance [139] assistance,job [139] job,opportunities Top Word Pairs in Tweet in G6:
[31] #supplychain,#logistics [21] supply,chain [20] #logistics,#supplychain [10] splitting,smart [9] two,#digital [9] #freightforwarder,#supplychain [7] supply,chains [7] #logistics,#trade [6] ice,cream [6] china,splitting Top Word Pairs in Tweet in G7:
[20] #transport,#supplychain [16] #supplychain,#logistics [15] #essentialsupplies,#supplychain [14] another,#tuttsclumpcider [14] #supplychain,#takecare [14] #takecare,#staysafe [14] #staysafe,#propercider [14] #logistique,#transport [13] #jobs,#supplychain [13] #tuttsclumpcider,bottle Top Word Pairs in Tweet in G8:
[21] supply,chain [9] grupot21,ðÿœž [8] #grupot21,#dhltf2020 [8] #dhltf2020,#transportationforum [8] #transportationforum,#transporte [8] #transporte,#cadenadesuministro [8] #cadenadesuministro,#supplychain [6] #supplychain,resiliency [6] ðÿœž,innovaciã [6] innovaciã,digitalizaciã Top Word Pairs in Tweet in G9:
[16] supply,chain [13] #procurement,#supplychain [11] supply,chains [9] #supplychain,direct [9] direct,impact [9] impact,#revenues [9] #revenues,#costs [9] #costs,#profitability [9] #profitability,#cashflow [9] #cashflow,#workingcapital Top Word Pairs in Tweet in G10:
[37] #supplychain,#logistics [16] supply,chain [16] #logistics,#supplychain [12] #supplychain,#3pl [11] #oneburris,#logistics [10] learn,more [10] ulehss,#supplychain [10] find,more [7] #transportation,#trucking [7] #trucking,#supplychain Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Tweeters in Entire Graph:
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Top Tweeters in G3:
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Top Tweeters in G10: