The graph represents a network of 621 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 3/15/2023 5:00:36 PM. The network was obtained from Twitter on Thursday, 16 March 2023 at 01:22 UTC.
The tweets in the network were tweeted over the 1728-day, 12-hour, 53-minute period from Thursday, 21 June 2018 at 10:22 UTC to Wednesday, 15 March 2023 at 23:16 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 : 621
Unique Edges : 402
Edges With Duplicates : 11717
Total Edges : 12119
Number of Edge Types : 8
Tweet : 328
Retweet : 2917
MentionsInRetweet : 3221
Quote : 14
MentionsInQuote : 15
Mentions : 5571
MentionsInReplyTo : 33
Replies to : 20
Self-Loops : 5145
Reciprocated Vertex Pair Ratio : 0.043859649122807
Reciprocated Edge Ratio : 0.0840336134453782
Connected Components : 176
Single-Vertex Connected Components : 110
Maximum Vertices in a Connected Component : 263
Maximum Edges in a Connected Component : 11435
Maximum Geodesic Distance (Diameter) : 12
Average Geodesic Distance : 4.148872
Graph Density : 0.00154537426627188
Modularity : 0.053937
NodeXL Version : 1.0.1.510
Data Import : The graph represents a network of 621 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 3/15/2023 5:00:36 PM. The network was obtained from Twitter on Thursday, 16 March 2023 at 01:22 UTC.
The tweets in the network were tweeted over the 1728-day, 12-hour, 53-minute period from Thursday, 21 June 2018 at 10:22 UTC to Wednesday, 15 March 2023 at 23:16 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:
[4312] #healthtech,#smartcity [4305] #digitalhealth,#web3 [4297] #csuite,#digitalhealth [4289] #datascientist,#csuite [4286] #vive2023,#healthtech [4286] #web3,#cx [3154] #smartcity,#ata2023 [3133] #ata2023,#datascientist [2629] chidambara09,#vive2023 [1832] #cx,#ehealth Top Word Pairs in Tweet in G1:
[4301] #healthtech,#smartcity [4294] #digitalhealth,#web3 [4286] #csuite,#digitalhealth [4278] #datascientist,#csuite [4277] #web3,#cx [4275] #vive2023,#healthtech [3144] #smartcity,#ata2023 [3123] #ata2023,#datascientist [2620] chidambara09,#vive2023 [1832] #cx,#ehealth Top Word Pairs in Tweet in G2:
[54] #vol,départ [50] #traveltech,#magellio [20] départ,#paris [20] #paris,#hotel [17] vol,hôtel [15] #portugal,#traveltech [15] #hotel,#portugal [13] réservez,maintenant [12] départ,#bordeaux [12] travel,industry Top Word Pairs in Tweet in G3:
[11] female,travelers [9] itb,berlin [7] #travel,tech [6] being,ignored [6] european,summit [6] #itbberlin,#traveltech [6] wayaway,wayaway [6] #rt,phocuswire [6] sure,#travel [6] company,wayaway Top Word Pairs in Tweet in G4:
[9] #marketing,#fashiontech [9] siyimaoart,#marketing [9] weekend,siyimaoart [9] #fintech,#ai [9] #chatgpt,#metaverse [9] #fashiontech,#fintech [9] #vr,painting [9] #ai,#chatgpt [9] #traveltech,weekend [7] enricomolinari,#vr Top Word Pairs in Tweet in G5:
[11] travel,tech [11] joshua,ryan [10] #digitalhealth,#web3 [10] #smartcity,#ata2023 [10] #ata2023,#datascientist [10] traveltech,event [10] #vive2023,#healthtech [10] #healthtech,#smartcity [10] #csuite,#digitalhealth [10] #datascientist,#csuite Top Word Pairs in Tweet in G6:
[43] advanced,#traveltech [43] anticipate,problems [43] problems,minimise [43] occ,uses [43] next,generation [43] generation,occ [43] #traveltech,anticipate [43] uses,advanced [42] explains,aluenterprise [42] aluenterprise,next Top Word Pairs in Tweet in G7:
[12] world,changing [12] tourismx's,blockchain [12] making,travel [12] way,travel [12] blockchain,technology [12] way,making [12] leading,way [12] technology,leading [12] changing,way [12] travel,tourismx's Top Word Pairs in Tweet in G8:
[3] #hostaway,#proptech [3] traveltech,hospitalitynet [2] dack,team [2] oxfordeconomics,showing [2] #vrma,#hostaway [2] team,#airbnb [2] bookingcom,help [2] finding,oxfordeconomics [2] hospitalitynet,highlights [2] partners,cheers Top Word Pairs in Tweet in G9:
[5] amadeus,microsoft [4] travel,tech [4] co,authored [4] next,generation [4] generation,travel [4] report,next [4] issue,report [4] microsoft,issue [3] thai,based [3] #superapp,robinhood Top Word Pairs in Tweet in G10:
[5] experience,#4yfn23 [5] hotelbeds,tell [5] asked,partner [5] tell,experience [5] #traveltechlab,told [5] partner,hotelbeds [5] #4yfn23,#traveltechlab [4] wayraes,asked [2] hotelbeds,telefonica Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G3:
Top Replied-To in G6:
Top Replied-To in G8:
Top Replied-To in G10:
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: