The graph represents a network of 586 Twitter users whose tweets in the requested range contained "fashiontech", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Thursday, 03 February 2022 at 06:56 UTC.
The requested start date was Thursday, 03 February 2022 at 01:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 7,500.
The tweets in the network were tweeted over the 4-day, 19-hour, 4-minute period from Friday, 28 January 2022 at 23:45 UTC to Wednesday, 02 February 2022 at 18:50 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 : 586
Unique Edges : 678
Edges With Duplicates : 14127
Total Edges : 14805
Number of Edge Types : 5
Retweet : 6064
MentionsInRetweet : 5515
Replies to : 31
Mentions : 3023
Tweet : 172
Self-Loops : 1448
Reciprocated Vertex Pair Ratio : 0.0541832669322709
Reciprocated Edge Ratio : 0.102796674225246
Connected Components : 56
Single-Vertex Connected Components : 32
Maximum Vertices in a Connected Component : 399
Maximum Edges in a Connected Component : 14391
Maximum Geodesic Distance (Diameter) : 6
Average Geodesic Distance : 2.812051
Graph Density : 0.00385928065108952
Modularity : 0.0694
NodeXL Version : 1.0.1.447
Data Import : The graph represents a network of 586 Twitter users whose tweets in the requested range contained "fashiontech", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Thursday, 03 February 2022 at 06:56 UTC.
The requested start date was Thursday, 03 February 2022 at 01:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 7,500.
The tweets in the network were tweeted over the 4-day, 19-hour, 4-minute period from Friday, 28 January 2022 at 23:45 UTC to Wednesday, 02 February 2022 at 18:50 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 : GraphServerTwitterSearch
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 : Betweenness Centrality
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[6265] #women,#ehealth [6261] #cx,#women [6211] #ces2023,#finserv [6191] #finserv,#fashiontech [5973] #ehealth,#data [5973] #data,#ces2023 [5954] #fashiontech,#insurtech [5664] #digital,#cx [5469] #datascientist,#digital [4548] chidambara09,#datascientist Top Word Pairs in Tweet in G1:
[4553] #women,#ehealth [4552] #cx,#women [4510] #ces2023,#finserv [4498] #finserv,#fashiontech [4380] #fashiontech,#insurtech [4334] #ehealth,#data [4334] #data,#ces2023 [4111] #digital,#cx [3988] #datascientist,#digital [2982] chidambara09,#datascientist Top Word Pairs in Tweet in G2:
[486] #ai,#datascientist [467] #datascientist,#bigdata [467] #bigdata,#machinelearning [436] #ces2023,#finserv [434] #finserv,#fashiontech [433] #cx,#women [433] #women,#ehealth [414] #ehealth,#data [414] #data,#ces2023 [406] #fashiontech,#insurtech Top Word Pairs in Tweet in G3:
[1198] #women,#ehealth [1195] #cx,#women [1185] #ces2023,#finserv [1178] #finserv,#fashiontech [1147] #ehealth,#data [1147] #data,#ces2023 [1103] chidambara09,#datascientist [1097] #digital,#cx [1097] #fashiontech,#insurtech [1049] #insurtech,#big Top Word Pairs in Tweet in G4:
[66] #nft,#nfts [66] #nfts,#nftcommunity [61] come,discord [61] discord,nfts [61] nfts,#nft [61] #nftcommunity,#cryptofashion [61] #cryptofashion,#nftwearables [60] neuno_io,come [60] #nftwearables,#f [35] #neuno,#nft Top Word Pairs in Tweet in G5:
[25] apple,watch [18] fashion,tech [13] watch,充電器 [12] 前回,圏外 [10] watch,充電 [9] ワイヤレス充電器,apple [9] 充電器,ワイヤレス充電器 [9] ワイヤレス充電器,スタンド [8] 充電,apple [8] 圏外,ワイヤレス充電器 Top Word Pairs in Tweet in G6:
[9] #nft,#sneakers [9] #sneakers,rage [9] rage,jacobwgallagher [9] jacobwgallagher,#digitalartist [9] #digitalartist,#fashiontech [9] #fashiontech,sharleneisenia [9] sharleneisenia,dahl_consult [9] dahl_consult,hana_elsayyed [8] anand_narang,#nft [8] hana_elsayyed,bet Top Word Pairs in Tweet in G7:
[20] cappasity,nfts [12] nfts,benefit [12] benefit,brands [12] brands,cappasity [12] nfts,change [12] change,way [12] way,brands [12] brands,engage [12] engage,customers [12] customers,dive Top Word Pairs in Tweet in G8:
[3] inexmoda,alejandroariasg [3] alejandroariasg,alcaldiademed [3] alcaldiademed,eleobe [3] eleobe,cebotero [3] cebotero,camaramedellin [3] camaramedellin,alianza [3] alianza,inexmoda [3] inexmoda,sapienciamed [2] acimedellin,inexmoda [2] sapienciamed,pe Top Word Pairs in Tweet in G9:
[4] online,class [2] 3d,printing [2] printing,fabric [2] fabric,wireless [2] wireless,leds [2] leds,excited [2] excited,teaching [2] teaching,another [2] another,online [2] class,makerfaire Top Word Pairs in Tweet in G10:
[80] #cx,#women [80] #women,#ehealth [80] #finserv,#fashiontech [79] #ces2023,#finserv [77] #ehealth,#data [77] #data,#ces2023 [71] #digital,#cx [70] chidambara09,#datascientist [70] #fashiontech,#insurtech [64] #datascientist,#digital Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G3:
Top Replied-To in G8:
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: