The graph represents a network of 309 Twitter users whose recent tweets contained "#FashionTech", 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 Monday, 16 January 2023 at 07:18 UTC.
The tweets in the network were tweeted over the 10-day, 0-hour, 23-minute period from Friday, 06 January 2023 at 05:55 UTC to Monday, 16 January 2023 at 06:19 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 : 309
Unique Edges : 1198
Edges With Duplicates : 558
Total Edges : 1756
Number of Edge Types : 5
Tweet : 83
Retweet : 176
MentionsInRetweet : 1206
Mentions : 283
Replies to : 8
Self-Loops : 95
Reciprocated Vertex Pair Ratio : 0.0611455108359133
Reciprocated Edge Ratio : 0.115244347191831
Connected Components : 56
Single-Vertex Connected Components : 34
Maximum Vertices in a Connected Component : 185
Maximum Edges in a Connected Component : 1517
Maximum Geodesic Distance (Diameter) : 6
Average Geodesic Distance : 2.83367
Graph Density : 0.0144054974152062
Modularity : 0.423207
NodeXL Version : 1.0.1.508
Data Import : The graph represents a network of 309 Twitter users whose recent tweets contained "#FashionTech", 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 Monday, 16 January 2023 at 07:18 UTC.
The tweets in the network were tweeted over the 10-day, 0-hour, 23-minute period from Friday, 06 January 2023 at 05:55 UTC to Monday, 16 January 2023 at 06:19 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 : #FashionTech
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 : In-Degree
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[30] #innovation,#fashiontech [28] pink,under [28] properties,dye [28] beige,pink [28] thanks,photochromic [28] #physics,#innovation [28] dress,goes [28] used,garment [28] goes,beige [28] dye,used Top Word Pairs in Tweet in G1:
[18] enilev,labordeolivier [17] frronconi,pawlowskimario [17] tamaramccleary,perilynn [17] nickystevo,sulefati7 [17] mary_gambara,nickystevo [16] nicochan33,curieuxexplorer [16] lorimoreno,jeroenbartelse [16] robot,flagship [16] louisvuitton,installs [16] kusama,painting Top Word Pairs in Tweet in G2:
[13] #bigdata,#analytics [11] eli_krumova,august12th_ [11] pinakilaskar,ingliguori [11] august12th_,cappasity [11] enilev,pinakilaskar [11] ingliguori,eli_krumova [11] #ai,#machinelearning [9] smaksked,imam_a_siddique [9] #machinelearning,#iot [9] #fashiontech,#bigdata Top Word Pairs in Tweet in G3:
[19] shi4tech,enilev [17] under,sunlight [17] properties,dye [17] mvollmer1,albertoemachado [17] ragusosergio,mvollmer1 [17] beige,pink [17] #fashiontech,chboursin [17] anand_narang,kalydeoo [17] kalydeoo,ragusosergio [17] dress,goes Top Word Pairs in Tweet in G4:
[12] fashion,industry [10] #metaverse,learn [10] #wearabletech,#metaverse [10] learn,more [10] #fashiontech,#digitaltransformation [10] happening,fashion [10] #fashionnft,#smartgarments [10] industry,answer [10] #smartgarments,#wearabletech [10] #web3,#fashionnft Top Word Pairs in Tweet in G5:
[5] #technology,#innovation [5] scoopit,#fashiontech [4] technology,trends [4] #ces2023,#ces [4] #fashiontech,#technology [4] fashion,industry [3] sharleneisenia,smaksked [3] spectacular,#fashiontech [3] helping,build [3] frronconi,labordeolivier Top Word Pairs in Tweet in G6:
[15] agressions,bomber [15] #nft,monde [15] #ces2023,#ces23ech [15] protéger,agressions [15] bomber,revolutionnaire [15] vivre,#ces2023 [15] tewoz,catherinelardy [15] revolutionnaire,protéger [15] lancer,bomber [15] #fashiontech,bad_biche Top Word Pairs in Tweet in G7:
[23] #virtualfashion,#fashiontech [23] #digitalfashion,#virtualfashion [18] dressxcom,dundasworld [18] #metaversegeneration,#digitalfashion [18] party,#metaverse [18] ready,party [18] roblox,ready [18] party,drop [18] dundasworld,party [18] drop,arrived Top Word Pairs in Tweet in G9:
[6] let's,discuss [6] 8030,let's [6] lab,booth [6] #3davatars,#digitaltwins [6] maximize,#customerexperience [6] #customerexperience,sap_io [6] booth,8030 [6] #retailtech,#fashiontech [6] innovation,lab [6] sap_io,sap Top Word Pairs in Tweet in G10:
[8] styles,endless [8] dress,question [8] herself,styles [8] #missuniverse,#71stmissuniverse [8] designer,herself [8] rely,designer [8] world,rely [8] endless,possibilities [8] question,remains [8] cocks,used Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
Top Replied-To in G5:
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 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: