The graph represents a network of 4,136 Twitter users whose recent tweets contained "supplychain", or who were replied to, mentioned, retweeted or quoted in those tweets, taken from a data set limited to a maximum of 5,000 tweets, tweeted between 3/26/2006 12:00:00 AM and 3/10/2023 5:00:35 PM. The network was obtained from Twitter on Saturday, 11 March 2023 at 20:34 UTC.
The tweets in the network were tweeted over the 2647-day, 7-hour, 24-minute period from Thursday, 10 December 2015 at 17:35 UTC to Saturday, 11 March 2023 at 01:00 UTC.
There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, an edge for each "retweet" relationship in a tweet, an edge for each "quote" relationship in a tweet, an edge for each "mention in retweet" relationship in a tweet, an edge for each "mention in reply-to" relationship in a tweet, an edge for each "mention in quote" relationship in a tweet, an edge for each "mention in quote reply-to" relationship in a tweet, and a self-loop edge for each tweet that is not from above.
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 : 4136
Unique Edges : 2919
Edges With Duplicates : 5871
Total Edges : 8790
Number of Edge Types : 9
Mentions : 1609
MentionsInRetweet : 2414
Tweet : 2468
Replies to : 192
MentionsInReplyTo : 200
Retweet : 1702
Quote : 71
MentionsInQuote : 107
MentionsInQuoteReply : 27
Self-Loops : 2862
Reciprocated Vertex Pair Ratio : 0.0324579521982886
Reciprocated Edge Ratio : 0.0628751071734781
Connected Components : 1550
Single-Vertex Connected Components : 1056
Maximum Vertices in a Connected Component : 811
Maximum Edges in a Connected Component : 2461
Maximum Geodesic Distance (Diameter) : 16
Average Geodesic Distance : 6.27844
Graph Density : 0.000204591647000765
Modularity : 0.460116
NodeXL Version : 1.0.1.510
Data Import : The graph represents a network of 4,136 Twitter users whose recent tweets contained "supplychain", or who were replied to, mentioned, retweeted or quoted in those tweets, taken from a data set limited to a maximum of 5,000 tweets, tweeted between 3/26/2006 12:00:00 AM and 3/10/2023 5:00:35 PM. The network was obtained from Twitter on Saturday, 11 March 2023 at 20:34 UTC.
The tweets in the network were tweeted over the 2647-day, 7-hour, 24-minute period from Thursday, 10 December 2015 at 17:35 UTC to Saturday, 11 March 2023 at 01:00 UTC.
There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, an edge for each "retweet" relationship in a tweet, an edge for each "quote" relationship in a tweet, an edge for each "mention in retweet" relationship in a tweet, an edge for each "mention in reply-to" relationship in a tweet, an edge for each "mention in quote" relationship in a tweet, an edge for each "mention in quote reply-to" relationship in a tweet, and a self-loop edge for each tweet that is not from above.
Layout Algorithm : The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.
Graph Source : TwitterSearch2
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:
[976] supply,chain [353] #logistics,#supplychain [228] link,bio [172] #weapons,#supplychain [172] working,defence [172] #china,infiltrate [172] defence,firms [172] britain,#weapons [172] firms,uk [172] infiltrate,britain Top Word Pairs in Tweet in G1:
[414] supply,chain [226] link,bio [141] click,link [120] cvs,health [102] #supplychain,job [85] #logistics,#supplychain [64] #supplychain,#logistics [56] bio,apply [55] see,latest [49] learn,more Top Word Pairs in Tweet in G2:
[171] britain,#weapons [171] #uk,government [171] government,working [171] firms,uk [171] defence,firms [171] #supplychain,#uk [171] #weapons,#supplychain [171] working,defence [171] #china,infiltrate [171] infiltrate,britain Top Word Pairs in Tweet in G3:
[42] #5g,#ai [42] #ces2023,#supplychain [42] #mobility,#iot [42] #innovation,#mobility [42] #ai,#tech [42] #transportation,#ces2023 [42] #iot,#5g [42] #tech,#transportation [42] #tech4good,#innovation [40] future,#tech4good Top Word Pairs in Tweet in G4:
[58] supply,chain [27] #supplychainnow,#supplychain [23] scottwluton,gregoryswhite [18] 12,noon [16] time,change [16] people,challenge [16] life,amy [16] lot,time [16] spend,lot [16] group,people Top Word Pairs in Tweet in G5:
[86] #supplychain,#unitedstates [86] #chineseinfluence,#influence [86] #china,#chineseinfluence [86] #supplychainmanagement,#counteringchina [86] #unitedstates,#supplychainmanagement [86] #influence,#supplychain [85] dr_adibenayati,#china [85] #counteringchina,#nationalsecuri Top Word Pairs in Tweet in G6:
[4] challenged,definition [4] adding,conversation [4] thought,leadership [4] companies,challenged [4] #midsize,companies [4] unsustainable,evolve [4] definition,unsustainable [4] #logistics,#supplychain [4] evolve,strategies [4] #supplychain,thought Top Word Pairs in Tweet in G7:
[20] mnw,dmtr [15] xep,electraprotocol [14] day,checking [14] validator,see [14] morpheus,validator [14] large,companies [14] customers,organizations [14] show,dashboard [14] organizations,show [14] checking,morpheus Top Word Pairs in Tweet in G8:
[50] supply,chain [33] #supplychainjobs,#supplychain [33] #supplychain,#supplychaincareers [15] #trasporti,#spedizioni [15] #shipping,#supplychain [15] #spedizioni,#shipping [15] #logistica,#trasporti [14] #export,#logistica [14] #import,#export [9] truck,driver Top Word Pairs in Tweet in G9:
[18] भ,रत [17] कर,र [12] ल,ए [12] ए,कर [12] क,ल [12] क,ब [12] ब,च [12] रत,क [11] ल,ई [11] ई,च Top Word Pairs in Tweet in G10:
[14] supply,chain [7] #supplychain,#logistics [5] promat,2023 [5] trading,partners [5] #alpine_sc,#supplychain [5] trading,partner [4] drive,efficiency [4] #supplychain,learn [4] helping,businesses [4] time,sign Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G6:
Top Replied-To in G7:
Top Replied-To in G8:
Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
Top Mentioned in G2:
Top Mentioned in G3:
Top Mentioned in G4:
Top Mentioned in G5:
Top Mentioned in G6:
Top Mentioned in G7:
Top Mentioned in G8:
Top Mentioned in G9:
Top Mentioned in G10:
Top Tweeters in Entire Graph:
Top Tweeters in G1:
Top Tweeters in G2:
Top Tweeters in G3:
Top Tweeters in G4:
Top Tweeters in G5:
Top Tweeters in G6:
Top Tweeters in G7:
Top Tweeters in G8:
Top Tweeters in G9:
Top Tweeters in G10: