The graph represents a network of 830 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, 09 June 2022 at 05:38 UTC.
The requested start date was Thursday, 09 June 2022 at 00:01 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 13-day, 16-hour, 58-minute period from Thursday, 26 May 2022 at 01:13 UTC to Wednesday, 08 June 2022 at 18:11 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 : 830
Unique Edges : 782
Edges With Duplicates : 12415
Total Edges : 13197
Number of Edge Types : 5
Retweet : 5241
MentionsInRetweet : 4712
Mentions : 2759
Tweet : 450
Replies to : 35
Self-Loops : 1731
Reciprocated Vertex Pair Ratio : 0.0497737556561086
Reciprocated Edge Ratio : 0.0948275862068965
Connected Components : 82
Single-Vertex Connected Components : 48
Maximum Vertices in a Connected Component : 649
Maximum Edges in a Connected Component : 12769
Maximum Geodesic Distance (Diameter) : 8
Average Geodesic Distance : 3.02812
Graph Density : 0.00236022497710989
Modularity : 0.095948
NodeXL Version : 1.0.1.449
Data Import : The graph represents a network of 830 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, 09 June 2022 at 05:38 UTC.
The requested start date was Thursday, 09 June 2022 at 00:01 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 13-day, 16-hour, 58-minute period from Thursday, 26 May 2022 at 01:13 UTC to Wednesday, 08 June 2022 at 18:11 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:
[3913] #cx,#women [3910] #datascientist,#mwc22 [3869] #women,#ehealth [3829] #mwc22,#ai [3764] #ehealth,#ces2023 [2127] #healthtech,#datascientist [1806] #digitalhealth,#datascientist [1753] #ai,#healthtech [1550] #healthtech,#ml [1541] #iiot,#cx Top Word Pairs in Tweet in G1:
[851] #ai,#machinelearning [699] #machinelearning,#selfdrivingcars [497] #selfdrivingcars,#autonomousvehicles [399] #bigdata,#analytics [341] #datascientist,#mwc22 [341] #cx,#women [335] #women,#ehealth [332] #mwc22,#ai [324] #ehealth,#ces2023 [312] #autonomousvehicles,#bigdata Top Word Pairs in Tweet in G2:
[2974] #cx,#women [2972] #datascientist,#mwc22 [2946] #women,#ehealth [2911] #mwc22,#ai [2867] #ehealth,#ces2023 [1605] #healthtech,#datascientist [1383] #digitalhealth,#datascientist [1348] #ai,#healthtech [1196] #healthtech,#ml [1188] #iiot,#cx Top Word Pairs in Tweet in G3:
[596] #cx,#women [595] #datascientist,#mwc22 [586] #women,#ehealth [584] #mwc22,#ai [573] #ehealth,#ces2023 [310] #healthtech,#datascientist [290] chidambara09,#healthtech [283] #digitalhealth,#datascientist [278] #ai,#healthtech [256] chidambara09,#digitalhealth Top Word Pairs in Tweet in G4:
[86] ãƒ,ム[22] apple,watch [21] fashion,tech [11] 前回,圏外 [10] ハンドソープ,ディスペンサー [10] 自動,泡 [10] #sibocolor,#sibostyle [10] #sibostyle,#stylingtool [10] #stylingtool,#fashionapp [10] #fashionapp,#personalbranding Top Word Pairs in Tweet in G5:
[54] #ai,#machinelearning [48] #machinelearning,#selfdrivingcars [33] #selfdrivingcars,#autonomousvehicles [23] #autonomousvehicles,#bigdata [23] #bigdata,#analytics [12] #vr,#ar [11] #analytics,#datascience [10] #datascientist,#bigdata [8] fashion,brands [7] #coding,#programming Top Word Pairs in Tweet in G6:
[8] gucci,#metaverse [8] #metaverse,surfacemag [8] surfacemag,#fashiontech [8] #fashiontech,#marketing [8] #marketing,#finserv [8] #finserv,#fintech [7] enricomolinari,gucci [7] #fintech,anthonyrocha [2] awareness,#metaverse [2] #metaverse,today Top Word Pairs in Tweet in G7:
[15] world,rely [14] styles,ž [14] ž,#fashiontech [8] #fashiontech,ž [6] styles,#fashiontech [6] world,relies [6] #betrendy,#fashiontech [5] child,deserves [5] deserves,right [5] right,thrive Top Word Pairs in Tweet in G8:
[11] ventures,#fashiontech [10] future,fashion [8] moon,rabbit [8] rabbit,ventures [7] fashion,moon [7] #fashiontech,full [7] full,speed [7] speed,stellar [7] stellar,duo [7] duo,glitchedninja2 Top Word Pairs in Tweet in G9:
[13] need,#fashiontech [13] #fashiontech,#digitaltransformation [13] #digitaltransformation,happening [13] happening,fashion [13] fashion,industry [12] industry,answer [12] answer,#digitalfashion [12] #digitalfashion,#web3 [12] #web3,#fashionnft [12] #fashionnft,#smartgarments Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Replied-To in G6:
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Top Replied-To in G10:
Top Mentioned in Entire Graph:
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Top Tweeters in Entire Graph:
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Top Tweeters in G5:
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Top Tweeters in G10: