The graph represents a network of 4,512 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, 20 December 2019 at 11:28 UTC.
The requested start date was Wednesday, 18 December 2019 at 01:01 UTC and the maximum number of tweets (going backward in time) was 5,000.
The tweets in the network were tweeted over the 16-hour, 1-minute period from Tuesday, 17 December 2019 at 09:00 UTC to Wednesday, 18 December 2019 at 01:01 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 : 4512
Unique Edges : 4304
Edges With Duplicates : 1784
Total Edges : 6088
Number of Edge Types : 3
Tweet : 3241
Mentions : 2615
Replies to : 232
Self-Loops : 3241
Reciprocated Vertex Pair Ratio : 0.0238189757840413
Reciprocated Edge Ratio : 0.0465296626599457
Connected Components : 2372
Single-Vertex Connected Components : 1671
Maximum Vertices in a Connected Component : 589
Maximum Edges in a Connected Component : 1353
Maximum Geodesic Distance (Diameter) : 21
Average Geodesic Distance : 8.226142
Graph Density : 0.000126709572031174
Modularity : 0.573836
NodeXL Version : 1.0.1.422
Data Import : The graph represents a network of 4,512 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, 20 December 2019 at 11:28 UTC.
The requested start date was Wednesday, 18 December 2019 at 01:01 UTC and the maximum number of tweets (going backward in time) was 5,000.
The tweets in the network were tweeted over the 16-hour, 1-minute period from Tuesday, 17 December 2019 at 09:00 UTC to Wednesday, 18 December 2019 at 01:01 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 : Betweenness Centrality
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[109] ecommerce,website [106] artificial,intelligence [100] 25,ways [100] ways,artificial [100] intelligence,helping [100] helping,ecommerce [100] ecommerce,marketers [88] check,gig [85] gig,fiverr [71] ve,found Top Word Pairs in Tweet in G1:
[81] check,gig [80] gig,fiverr [70] artificial,intelligence [67] 25,ways [67] ways,artificial [67] intelligence,helping [67] helping,ecommerce [67] ecommerce,marketers [51] ecommerce,website [35] store,website Top Word Pairs in Tweet in G2:
[71] ve,found [71] found,solutions [71] solutions,work [71] work,well [71] well,cut [71] cut,hidden [71] hidden,costs [71] costs,ecommerce [5] #retail,#ecommerce [5] boost,sales Top Word Pairs in Tweet in G3:
[44] look,found [44] found,ebay [44] ebay,ebay [44] ebay,#domains [44] #domains,domain [44] domain,#business [44] #business,#startups [44] #startups,#branding [6] used,working [4] check,sony Top Word Pairs in Tweet in G4:
[9] encourage,#fastfashion [9] #fastfashion,consumption [9] consumption,still [9] still,good [9] good,hear [9] hear,ecommerce [9] ecommerce,behemoth [9] behemoth,asos [9] asos,set [8] aplastic_planet,encourage Top Word Pairs in Tweet in G5:
[27] welcome,#future [27] #future,#efood [27] #efood,delivery [27] delivery,ty [27] ty,intengineering [27] intengineering,enricomolinari [27] enricomolinari,#ecommerce [27] #ecommerce,#retailtech [26] enricomolinari,welcome [26] #retailtech,#marketing Top Word Pairs in Tweet in G6:
[22] traders,country [22] country,teamcait [22] teamcait,observe [22] observe,traders [22] traders,families [22] families,dharna [22] dharna,24 [22] 24,dec [22] dec,one [22] one,day Top Word Pairs in Tweet in G7:
[29] #ecommerce,#prestashop [29] #prestashop,#seo [29] #seo,#php [28] #php,#webdev [25] #webdev,#symfony [24] #symfony,#vuejs [22] #vuejs,#css [15] #css,#javascript [12] #javascript,#git [12] #websitedesign,#webdesign Top Word Pairs in Tweet in G8:
[18] #ecommerce,business [12] building,successful [12] successful,#ecommerce [12] business,easy [12] easy,feat [12] feat,know [12] know,challenges [12] challenges,faced [12] faced,ecommerce [9] #ecommerce,#retail Top Word Pairs in Tweet in G9:
[14] looking,professional [14] professional,website [14] website,problem [14] problem,design [14] design,attractive [14] attractive,one [14] one,affordable [14] affordable,price [13] hey,looking [9] predictions,2020 Top Word Pairs in Tweet in G10:
[28] 25,ways [28] ways,artificial [28] artificial,intelligence [28] intelligence,helping [28] helping,ecommerce [28] ecommerce,marketers [23] marketers,jeffbullas [4] marketers,#artificialintelligence [4] business,shoestring [4] shoestring,budget Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
Top Mentioned in G2:
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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:
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Top Tweeters in G5:
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Top Tweeters in G9:
Top Tweeters in G10: