The graph represents a network of 48 Twitter users whose tweets in the requested range contained "traveltech", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Thursday, 17 November 2022 at 02:18 UTC.
The requested start date was Thursday, 17 November 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 15-hour, 24-minute period from Thursday, 03 November 2022 at 03:14 UTC to Thursday, 03 November 2022 at 18:38 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 : 48
Unique Edges : 32
Edges With Duplicates : 42
Total Edges : 74
Number of Edge Types : 4
Retweet : 16
MentionsInRetweet : 23
Mentions : 17
Tweet : 18
Self-Loops : 18
Reciprocated Vertex Pair Ratio : 0.0555555555555556
Reciprocated Edge Ratio : 0.105263157894737
Connected Components : 19
Single-Vertex Connected Components : 9
Maximum Vertices in a Connected Component : 12
Maximum Edges in a Connected Component : 22
Maximum Geodesic Distance (Diameter) : 5
Average Geodesic Distance : 1.634855
Graph Density : 0.0168439716312057
Modularity : 0.515294
NodeXL Version : 1.0.1.507
Data Import : The graph represents a network of 48 Twitter users whose tweets in the requested range contained "traveltech", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Thursday, 17 November 2022 at 02:18 UTC.
The requested start date was Thursday, 17 November 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 15-hour, 24-minute period from Thursday, 03 November 2022 at 03:14 UTC to Thursday, 03 November 2022 at 18:38 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 : 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:
[72] ✈ï,✈ï [4] fri,yay [4] yay,sneak [4] work,citizens [4] airlines,signed [4] zone,day [4] signed,ndc [4] day,training [4] 19,airlines [4] architects,engineers Top Word Pairs in Tweet in G1:
[2] #leadership,discussion [2] moderate,one [2] future,travelâ [2] travelâ,november [2] landing,future [2] management,solution [2] leading,reservations [2] wbe_travel,skypathrecruit [2] excited,moderate [2] travel,studio Top Word Pairs in Tweet in G2:
[2] #makeitpossible,download [2] #journeyheroapp,#traveltech [2] letzte,chance [2] download,#travelapp [2] #traveltech,#travelinnovated [2] chance,luefty [2] #travelapp,#journeyheroapp Top Word Pairs in Tweet in G3:
[4] fri,yay [4] having,airport [4] yay,sneak [4] architects,engineers [4] sneak,peek [4] peek,architects [4] work,citizens [4] citizens,having [4] engineers,work [3] airport,fly_waâ Top Word Pairs in Tweet in G4:
[72] ✈ï,✈ï [4] yes,19 [4] 19,airlines [4] ✈ï,yes [4] signed,ndc [4] airlines,signed [3] travelport,✈ï Top Word Pairs in Tweet in G7:
[3] rebranding,web [3] working,rebranding [3] division,dft_uk [3] we've,working [3] dft_uk,market [3] behind,scenes [3] scenes,we've [3] web,design [3] design,division [2] billianit,behind Top Word Pairs in Tweet in G8:
[2] thanks,biometric [2] passport,thanks [2] tech,travelleisure [2] soon,passport [2] face,soon [2] biometric,tech [2] travelleisure,#traveltech Top Word Pairs in Tweet in G9:
[2] very,excited [2] announce,another [2] excited,see [2] much,phocuswire [2] another,successful [2] partnership,very [2] excited,announce [2] phocuswire,excited [2] thanks,much [2] successful,partnership Top Word Pairs in Tweet in G10:
[2] mo,innovar [2] cã,mo [2] xito,equipo [2] innovar,xito [2] vienen,digitalizaciã [2] digitalizaciã,agencias [2] viajes,2023 [2] quã,tendencias [2] 2023,cã [2] agencias,viajes Top Mentioned in Entire Graph:
Top Mentioned in G1:
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: