The graph represents a network of 10,608 Twitter users whose recent tweets contained "#eCommerce", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 18,000 tweets. The network was obtained from Twitter on Tuesday, 19 November 2019 at 08:13 UTC.
The tweets in the network were tweeted over the 5-day, 9-hour, 45-minute period from Wednesday, 13 November 2019 at 21:05 UTC to Tuesday, 19 November 2019 at 06:50 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 : 10608
Unique Edges : 15477
Edges With Duplicates : 11212
Total Edges : 26689
Self-Loops : 9041
Reciprocated Vertex Pair Ratio : 0.027662616154396
Reciprocated Edge Ratio : 0.0538359880364471
Connected Components : 3307
Single-Vertex Connected Components : 2276
Maximum Vertices in a Connected Component : 5081
Maximum Edges in a Connected Component : 17658
Maximum Geodesic Distance (Diameter) : 20
Average Geodesic Distance : 6.844118
Graph Density : 0.000127773912358454
Modularity : 0.552157
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 10,608 Twitter users whose recent tweets contained "#eCommerce", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 18,000 tweets. The network was obtained from Twitter on Tuesday, 19 November 2019 at 08:13 UTC.
The tweets in the network were tweeted over the 5-day, 9-hour, 45-minute period from Wednesday, 13 November 2019 at 21:05 UTC to Tuesday, 19 November 2019 at 06:50 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 : TwitterSearch
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
Vertex Alpha : Followers
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[2511] gt,gt [1004] e,commerce [561] #ecommerce,#christmas [560] check,out [469] #ecommerce,#marketing [458] #business,#ecommerce [448] t,co [447] https,t [427] mikequindazzi,gt [380] #retail,#ecommerce Top Word Pairs in Tweet in G1:
[269] e,commerce [126] check,out [93] #kedaiwebco,retweet [93] retweet,menang [93] menang,rm2 [93] rm2,di [93] di,store [93] store,anda [93] anda,#usahawan [93] #usahawan,#ecommerce Top Word Pairs in Tweet in G2:
[2295] gt,gt [415] mikequindazzi,gt [254] gt,#ai [247] #ecommerce,#fintech [234] gt,mikequindazzi [220] #ai,#ecommerce [169] #ai,#iot [139] #ecommerce,#robotics [139] #robotics,#onlineshopping [139] #onlineshopping,#fintech Top Word Pairs in Tweet in G3:
[81] e,commerce [67] pour,savoir [67] savoir,plus [56] sur,#ecommerce [41] #ecommerce,#retail [35] pour,s'inscrire [35] #cdiscount,78 [35] 78,57 [35] visites,#fnac [35] #fnac,38 Top Word Pairs in Tweet in G4:
[487] #ecommerce,#christmas [325] #sale,#tips [325] #tips,#deals [321] #business,#ecommerce [287] #shopping,#shop [287] #shop,#sale [287] #deals,#business [266] #seo,#smm [211] #ecommerce,#prestashop [205] #php,#webdev Top Word Pairs in Tweet in G5:
[102] check,out [85] #ebay,#ebayseller [85] #ebaystore,#reseller [84] ebay,#ebay [83] #ecommerce,#prestashop [83] #prestashop,#seo [83] #seo,#php [83] #php,#webdev [83] #webdev,#symfony [83] #symfony,#vuejs Top Word Pairs in Tweet in G6:
[43] e,commerce [43] click,here [41] check,out [30] #ecommerce,#marketing [29] here,more [28] #ecommerce,business [27] find,out [24] out,here [22] more,info [21] #ecommerce,#smallbusiness Top Word Pairs in Tweet in G7:
[43] e,commerce [40] #digitalmarketing,#seo [38] #ecommerce,#startup [36] #ecommerce,#retail [35] #startup,#ecommerce [28] #marketing,#digitalmarketing [28] #retail,#ecommerce [25] online,store [22] digital,marketing [21] #entrepreneur,#startup Top Word Pairs in Tweet in G8:
[52] 19,20 [48] https,t [48] t,co [45] tu,#ecommerce [44] sobre,#ecommerce [43] 20,noviembre [40] #ecommerce,#monetización [37] congreso,online [35] llega,4º [35] 4º,edición Top Word Pairs in Tweet in G9:
[211] india,s [171] fdi,policy [130] s,retail [130] retail,trade [75] against,#ecommerce [74] call,7 [74] 7,crore [74] crore,traders [74] traders,india [74] india,come Top Word Pairs in Tweet in G10:
[25] magento,2 [19] #magento,#magento2 [19] #magento2,#ecommerce [15] customer,experience [14] #magento,2 [12] #magento,#ecommerce [11] magento,commerce [11] #mageplaza,#magento [11] #ecommerce,flagbit [10] don,t Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
Top Replied-To in G3:
Top Replied-To in G4:
Top Replied-To in G5:
Top Replied-To in G6:
Top Replied-To in G7:
Top Replied-To in G8:
Top Replied-To in G9:
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: