The graph represents a network of 541 Twitter users whose recent tweets contained "traveltech", or who were replied to, mentioned, retweeted or quoted in those tweets, taken from a data set limited to a maximum of 5,000 tweets, tweeted between 3/26/2006 12:00:00 AM and 3/8/2023 5:00:33 PM. The network was obtained from Twitter on Thursday, 09 March 2023 at 02:22 UTC.
The tweets in the network were tweeted over the 1721-day, 12-hour, 44-minute period from Thursday, 21 June 2018 at 10:22 UTC to Wednesday, 08 March 2023 at 23:07 UTC.
There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, an edge for each "retweet" relationship in a tweet, an edge for each "quote" relationship in a tweet, an edge for each "mention in retweet" relationship in a tweet, an edge for each "mention in reply-to" relationship in a tweet, an edge for each "mention in quote" relationship in a tweet, an edge for each "mention in quote reply-to" relationship in a tweet, and a self-loop edge for each tweet that is not from above.
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 : 541
Unique Edges : 402
Edges With Duplicates : 11645
Total Edges : 12047
Number of Edge Types : 8
Tweet : 229
Retweet : 3064
MentionsInRetweet : 3408
Mentions : 5289
Replies to : 12
MentionsInReplyTo : 24
Quote : 10
MentionsInQuote : 11
Self-Loops : 4845
Reciprocated Vertex Pair Ratio : 0.0550621669626998
Reciprocated Edge Ratio : 0.104377104377104
Connected Components : 136
Single-Vertex Connected Components : 91
Maximum Vertices in a Connected Component : 281
Maximum Edges in a Connected Component : 11572
Maximum Geodesic Distance (Diameter) : 13
Average Geodesic Distance : 4.09099
Graph Density : 0.00203327171903882
Modularity : 0.0515
NodeXL Version : 1.0.1.510
Data Import : The graph represents a network of 541 Twitter users whose recent tweets contained "traveltech", or who were replied to, mentioned, retweeted or quoted in those tweets, taken from a data set limited to a maximum of 5,000 tweets, tweeted between 3/26/2006 12:00:00 AM and 3/8/2023 5:00:33 PM. The network was obtained from Twitter on Thursday, 09 March 2023 at 02:22 UTC.
The tweets in the network were tweeted over the 1721-day, 12-hour, 44-minute period from Thursday, 21 June 2018 at 10:22 UTC to Wednesday, 08 March 2023 at 23:07 UTC.
There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, an edge for each "retweet" relationship in a tweet, an edge for each "quote" relationship in a tweet, an edge for each "mention in retweet" relationship in a tweet, an edge for each "mention in reply-to" relationship in a tweet, an edge for each "mention in quote" relationship in a tweet, an edge for each "mention in quote reply-to" relationship in a tweet, and a self-loop edge for each tweet that is not from above.
Layout Algorithm : The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.
Graph Source : TwitterSearch2
Graph Term : traveltech
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:
[4405] #healthtech,#smartcity [4397] #vive2023,#healthtech [4389] #digitalhealth,#web3 [4382] #csuite,#digitalhealth [4362] #web3,#cx [4351] #datascientist,#csuite [4321] #smartcity,#ata2023 [4267] #ata2023,#datascientist [2802] chidambara09,#vive2023 [1802] #cx,#ehea Top Word Pairs in Tweet in G1:
[4375] #healthtech,#smartcity [4367] #vive2023,#healthtech [4360] #digitalhealth,#web3 [4352] #csuite,#digitalhealth [4335] #web3,#cx [4321] #datascientist,#csuite [4291] #smartcity,#ata2023 [4237] #ata2023,#datascientist [2775] chidambara09,#vive2023 [1775] #cx,#ehea Top Word Pairs in Tweet in G2:
[38] #vol,départ [35] #traveltech,#magellio [15] #portugal,#traveltech [15] #hotel,#portugal [15] départ,#paris [15] #paris,#hotel [13] vol,hôtel [11] #hotel,#espagne [11] #espagne,#traveltech [8] #ponts,#mai Top Word Pairs in Tweet in G3:
[25] #fintech,#ai [25] #fashiontech,#fintech [25] #traveltech,weekend [25] #vr,painting [25] #ai,#chatgpt [25] #chatgpt,#metaverse [25] weekend,siyimaoart [25] siyimaoart,#marketing [25] #marketing,#fashiontech [23] enricomolinari,#vr Top Word Pairs in Tweet in G4:
[8] european,summit [6] feefo_official,bywaytravel [6] see,tomorrow [6] travolution,european [5] tomorrow,travolution [5] melt_digital,hotelbeds [5] bywaytravel,melt_digital [5] summit,wetravel [5] wetravel,feefo_official [5] hotelbeds,easyjet Top Word Pairs in Tweet in G5:
[9] itb,berlin [4] #itbberlin,#traveltech [3] authored,report [3] technologies,make [3] #technology,#innovation [3] #travel,#hospitality [3] co,authored [3] itb_berlin,march [2] #innovation,#awards [2] quicker,take Top Word Pairs in Tweet in G6:
[18] #datascientist,#csuite [18] #smartcity,#ata2023 [18] #digitalhealth,#web3 [18] #healthtech,#smartcity [18] #vive2023,#healthtech [18] #ata2023,#datascientist [18] #csuite,#digitalhealth [16] #cx,#ehea [16] #web3,#cx [16] chidambara09,#vive2023 Top Word Pairs in Tweet in G7:
[26] anticipate,problems [26] #traveltech,anticipate [26] next,generation [26] advanced,#traveltech [26] generation,occ [26] occ,uses [26] uses,advanced [26] problems,minimise [25] explains,aluenterprise [25] aluenterprise,next Top Word Pairs in Tweet in G8:
[11] #crossborderpayments,#eventstech [11] #traveltech,#blockchain [11] #retailtech,#crossborderpayments [11] #transittech,#traveltech [11] #eventstech,#transittech [11] #paytech,#medtech [11] #enterprise,#paytech [11] #medtech,#retailtech [11] #fintech,#enterprise [10] emphasispay,#fintech Top Word Pairs in Tweet in G9:
[2] finding,oxfordeconomics [2] oxfordeconomics,bookingcom [2] traveltech,hospitalitynet [2] oxfordeconomics,research [2] hospitalitynet,oxfordeconomics [2] comments,usdot's [2] bookingcom,finding Top Word Pairs in Tweet in G10:
[5] titans,award [5] thrilled,announce [5] announce,launch [5] launch,travel [5] game,changers [5] travel,tech [5] re,thrilled [5] highlight,game [5] tech,titans [4] award,meant Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G4:
Top Replied-To in G5:
Top Replied-To in G7:
Top Replied-To in G9:
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: