The graph represents a network of 1,000 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, 27 January 2022 at 06:58 UTC.
The requested start date was Thursday, 27 January 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 11-day, 20-hour, 0-minute period from Friday, 14 January 2022 at 22:59 UTC to Wednesday, 26 January 2022 at 19:00 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 : 1000
Unique Edges : 1776
Edges With Duplicates : 16404
Total Edges : 18180
Number of Edge Types : 5
Tweet : 406
Retweet : 5879
MentionsInRetweet : 7806
Mentions : 4018
Replies to : 71
Self-Loops : 1601
Reciprocated Vertex Pair Ratio : 0.0676923076923077
Reciprocated Edge Ratio : 0.126801152737752
Connected Components : 108
Single-Vertex Connected Components : 68
Maximum Vertices in a Connected Component : 811
Maximum Edges in a Connected Component : 17821
Maximum Geodesic Distance (Diameter) : 10
Average Geodesic Distance : 2.985128
Graph Density : 0.00312612612612613
Modularity : 0.109365
NodeXL Version : 1.0.1.447
Data Import : The graph represents a network of 1,000 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, 27 January 2022 at 06:58 UTC.
The requested start date was Thursday, 27 January 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 11-day, 20-hour, 0-minute period from Friday, 14 January 2022 at 22:59 UTC to Wednesday, 26 January 2022 at 19:00 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:
[4931] #women,#ehealth [4925] #cx,#women [4639] #finserv,#fashiontech [4595] #digital,#cx [4571] #datascientist,#digital [4392] #fashiontech,#insurtech [4354] #ces2023,#finserv [4135] #ehealth,#data [4111] #data,#ces2023 [3068] chidambara09,#datascientist Top Word Pairs in Tweet in G1:
[3964] #cx,#women [3963] #women,#ehealth [3719] #finserv,#fashiontech [3685] #digital,#cx [3669] #datascientist,#digital [3536] #fashiontech,#insurtech [3502] #ces2023,#finserv [3316] #ehealth,#data [3298] #data,#ces2023 [2292] chidambara09,#datascientist Top Word Pairs in Tweet in G2:
[431] #cx,#women [431] #women,#ehealth [419] #finserv,#fashiontech [407] #digital,#cx [404] #ces2023,#finserv [401] #datascientist,#digital [398] #fashiontech,#insurtech [391] #ehealth,#data [389] #data,#ces2023 [370] chidambara09,#datascientist Top Word Pairs in Tweet in G3:
[381] #datascientist,#bigdata [354] #ai,#datascientist [317] #bigdata,#machinelearning [247] #machinelearning,#analytics [216] #women,#ehealth [213] #cx,#women [203] #finserv,#fashiontech [199] #digital,#cx [198] #datascientist,#digital [196] #ces2023,#finserv Top Word Pairs in Tweet in G4:
[317] #women,#ehealth [313] #cx,#women [301] #digital,#cx [300] #datascientist,#digital [294] #finserv,#fashiontech [273] #fashiontech,#insurtech [250] #ces2023,#finserv [241] #ehealth,#data [238] #data,#ces2023 [231] chidambara09,#datascientist Top Word Pairs in Tweet in G5:
[124] apple,watch [87] watch,充電器 [51] アップルウォッチ,充電器 [46] 充電器,apple [39] ワイヤレス充電器,apple [37] 充電器,ワイヤレス充電器 [37] ワイヤレス充電器,スタンド [37] 置くだけ,充電器 [33] 充電器,アップルウォッチ [30] fashion,tech Top Word Pairs in Tweet in G6:
[7] #vr,#ar [7] cedric_o,chidambara09 [6] #prada,teams [6] teams,#adidas [6] #adidas,launch [6] launch,first [6] first,#nft [6] #nft,hint [6] hint,#beeple [6] #beeple,style Top Word Pairs in Tweet in G7:
[21] online,class [15] 3d,printing [15] printing,fabric [15] excited,teaching [15] teaching,another [15] another,online [13] need,#fashiontech [13] #fashiontech,#digitaltransformation [13] #digitaltransformation,happening [13] happening,fashion Top Word Pairs in Tweet in G8:
[42] world,relies [41] relies,styles [27] styles,#fashiontech [19] styles,create [19] create,inspire [19] inspire,fashion [19] fashion,styles [19] styles,visit [12] august12th_,world [10] hero_singx,world Top Word Pairs in Tweet in G9:
[14] exploring,features [14] features,opportunities [14] opportunities,metaverses [14] metaverses,retailers [14] retailers,wonder [14] wonder,digital [14] digital,universes [14] universes,impact [12] impact,onl [11] cappasity,exploring Top Word Pairs in Tweet in G10:
[16] #sibocolor,#sibostyle [16] #sibostyle,#stylingtool [15] #stylingtool,#fashionapp [13] #fashionapp,#sustainablefashion [13] learn,more [12] #sustainablefashion,#personalbranding [12] #stylistinyourpocket,#lifestylist [12] #lifestylist,#substandble [12] #substandble,#imageconsultant [12] #technology,#fashion Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Replied-To in G5:
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Top Replied-To in G8:
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:
Top Tweeters in G2:
Top Tweeters in G3:
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Top Tweeters in G5:
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Top Tweeters in G9:
Top Tweeters in G10: