The graph represents a network of 5,059 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 Sunday, 29 November 2020 at 21:02 UTC.
The requested start date was Saturday, 28 November 2020 at 01:01 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, 2-hour, 27-minute period from Monday, 23 November 2020 at 22:25 UTC to Saturday, 28 November 2020 at 00:53 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 : 5059
Unique Edges : 4253
Edges With Duplicates : 9178
Total Edges : 13431
Number of Edge Types : 5
Tweet : 3485
Mentions : 2478
Retweet : 2937
MentionsInRetweet : 4384
Replies to : 147
Self-Loops : 3607
Reciprocated Vertex Pair Ratio : 0.0379605508001489
Reciprocated Edge Ratio : 0.0731444962352098
Connected Components : 1448
Single-Vertex Connected Components : 980
Maximum Vertices in a Connected Component : 2472
Maximum Edges in a Connected Component : 8300
Maximum Geodesic Distance (Diameter) : 15
Average Geodesic Distance : 6.15238
Graph Density : 0.000217989214028126
Modularity : 0.437514
NodeXL Version : 1.0.1.441
Data Import : The graph represents a network of 5,059 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 Sunday, 29 November 2020 at 21:02 UTC.
The requested start date was Saturday, 28 November 2020 at 01:01 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, 2-hour, 27-minute period from Monday, 23 November 2020 at 22:25 UTC to Saturday, 28 November 2020 at 00:53 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:
[973] supply,chain [596] link,bio [369] #supplychain,#logistics [346] click,link [309] #supplychain,job [266] #logistics,#supplychain [205] supply,chains [182] covid,19 [176] see,latest [157] bio,see Top Word Pairs in Tweet in G1:
[588] link,bio [331] click,link [297] #supplychain,job [253] supply,chain [163] see,latest [156] bio,see [143] #supplychain,#logistics [134] bio,apply [125] latest,#supplychain [110] recommend,anyone Top Word Pairs in Tweet in G2:
[116] supply,chain [30] #logistics,#supplychain [26] supply,chains [20] covid,19 [18] learn,more [16] #supplychain,#warehousing [15] keeping,#supplychain [14] #supplychain,leaders [14] #supplychain,moving [13] cold,chain Top Word Pairs in Tweet in G3:
[141] mmortson,mmortson [66] ronald_vanloon,factory [59] factory,tomorrow [58] #iot,#ml [56] tasty,byte [56] byte,#datascience [56] #datascience,driving [56] driving,customer [56] customer,choice [56] choice,without Top Word Pairs in Tweet in G4:
[42] supply,chain [22] scottwluton,gregoryswhite [14] gregoryswhite,welcome [12] #customerexperience,management [12] management,quickly [12] quickly,grown [12] grown,one [12] one,important [12] important,areas [12] areas,#investment Top Word Pairs in Tweet in G5:
[29] supply,chain [24] #iot,#supplychain [18] #supplychain,management [13] #bigdata,#datascience [13] iot,helps [13] helps,predict [13] predict,avoid [13] avoid,waste [13] waste,perishable [13] perishable,foods Top Word Pairs in Tweet in G6:
[113] zebra,savanna [113] savanna,#iota [113] #iota,introduce [113] introduce,track [113] track,trace [113] trace,ledger [113] ledger,api [113] api,combines [113] combines,barcodes [113] barcodes,rfid Top Word Pairs in Tweet in G7:
[53] #supplychain,#logistics [46] supply,chain [18] #logistics,#supplychain [15] covid,19 [14] #vacante,#vacantes [14] aplica,gt [14] gt,co [13] #supplychainmanagement,#logisticsmanagement [13] #logisticsmanagement,#esourcing [13] #esourcing,#logurultd Top Word Pairs in Tweet in G8:
[75] supply,chains [48] digital,technology [48] technology,create [48] create,supply [48] chains,fix [48] fix,problems [48] problems,make [48] make,decisions [48] decisions,without [48] without,human Top Word Pairs in Tweet in G9:
[78] follow,edgistify [44] supply,chain [30] edgistify,regular [29] #supplychain,#logistics [24] #logistics,industry [21] regular,#updates [21] #updates,#supplychain [19] #digitalsupplychain,#warehousing [17] industry,#digitalsupplychain [16] edgistify,regula Top Word Pairs in Tweet in G10:
[18] supply,chain [10] covid,19 [8] supply,chains [8] black,friday [7] #shipping,#supplychain [7] #supplychain,#logistics [7] 19,vaccine [7] vaccine,distribution [7] distribution,task [7] task,poses 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:
Top Tweeters in G1:
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Top Tweeters in G10: