The graph represents a network of 4,656 Twitter users whose tweets in the requested range contained "ecommerce", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 25 October 2019 at 07:30 UTC.
The requested start date was Wednesday, 23 October 2019 at 00:01 UTC and the maximum number of tweets (going backward in time) was 5,000.
The tweets in the network were tweeted over the 15-hour, 26-minute period from Tuesday, 22 October 2019 at 08:34 UTC to Wednesday, 23 October 2019 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 : 4656
Unique Edges : 4614
Edges With Duplicates : 1934
Total Edges : 6548
Number of Edge Types : 3
Tweet : 2945
Mentions : 3393
Replies to : 210
Self-Loops : 2945
Reciprocated Vertex Pair Ratio : 0.025215448451963
Reciprocated Edge Ratio : 0.0491905354919054
Connected Components : 2130
Single-Vertex Connected Components : 1463
Maximum Vertices in a Connected Component : 635
Maximum Edges in a Connected Component : 1263
Maximum Geodesic Distance (Diameter) : 20
Average Geodesic Distance : 7.291194
Graph Density : 0.000148198183234227
Modularity : 0.610923
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 4,656 Twitter users whose tweets in the requested range contained "ecommerce", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 25 October 2019 at 07:30 UTC.
The requested start date was Wednesday, 23 October 2019 at 00:01 UTC and the maximum number of tweets (going backward in time) was 5,000.
The tweets in the network were tweeted over the 15-hour, 26-minute period from Tuesday, 22 October 2019 at 08:34 UTC to Wednesday, 23 October 2019 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 : ecommerce
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
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[422] gt,gt [217] e,commerce [171] check,out [147] create,high [147] hello,looking [147] looking,website [147] website,designer [146] designer,create [139] high,performance [127] performance,experience Top Word Pairs in Tweet in G1:
[87] check,out [79] e,commerce [59] out,gig [58] gig,fiverr [57] online,store [48] ecommerce,business [46] fiverr,develop [45] design,ecommerce [43] ecommerce,online [43] develop,design Top Word Pairs in Tweet in G2:
[353] gt,gt [80] mikequindazzi,gt [59] use,cases [59] gt,#ai [55] over,50 [55] 50,#blockchain [55] #blockchain,use [55] cases,gt [55] gt,medium [55] medium,mikequindazzi Top Word Pairs in Tweet in G3:
[147] hello,looking [147] looking,website [147] website,designer [146] designer,create [146] create,high [139] high,performance [127] performance,experience [109] experience,dependable [102] dependable,designer [47] hello,image Top Word Pairs in Tweet in G4:
[11] stephenkraussf,retailgeek [5] black,friday [5] e,commerce [5] #stateofecomm,#mmaweb [5] vidéo,amazon [5] amazon,utilise [5] utilise,ds [5] ds,1er [5] 1er,site [5] site,robotisée Top Word Pairs in Tweet in G5:
[51] #drones,ty [51] ty,wef [51] wef,enricomolinari [51] #ai,#retailtech [51] #retailtech,#ecommerce [51] #ecommerce,#finserv [50] iceland,takeaways [50] takeaways,now [50] now,delivered [50] delivered,#drones Top Word Pairs in Tweet in G6:
[19] ecom_nationfr,vous [15] à,l'international [13] #ecommerce,découvrez [12] e,forum [12] forum,2019 [12] 2019,louvière [12] sur,mesure [12] mesure,une [12] une,expérience [12] expérience,client Top Word Pairs in Tweet in G7:
[15] d_n_d,#mleu [14] magento,live [12] adobe,magento [8] cc,groupesmile [7] come,booth [7] booth,c4 [6] import,export [6] #mleu,#mleu19 [5] #magento,2 [5] magento,2 Top Word Pairs in Tweet in G8:
[31] recieved,additional [31] additional,funding [31] funding,new [31] new,respective [31] respective,partners [31] partners,commenced [31] commenced,minor [31] minor,developments [30] nirxcoin,recieved [30] developments,#ecommerce Top Word Pairs in Tweet in G9:
[7] #magento,#ecommerce [5] #khosting,met [5] met,new [5] new,wonderful [5] wonderful,friends [5] friends,#mleu [5] #mleu,sham [5] sham,paulnrogers [5] paulnrogers,vervaunt [5] vervaunt,#magento Top Word Pairs in Tweet in G10:
[44] bitzon,change [44] change,way [44] way,commerce [44] commerce,online [44] online,functions [44] functions,making [44] making,more [44] more,affordable [44] affordable,buyers [44] buyers,sellers Top Replied-To in Entire Graph:
Top Replied-To in G3:
Top Replied-To in G4:
Top Replied-To in G9:
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: