The graph represents a network of 823 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, 18 June 2020 at 01:48 UTC.
The requested start date was Thursday, 18 June 2020 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 13-day, 21-hour, 32-minute period from Thursday, 04 June 2020 at 00:36 UTC to Wednesday, 17 June 2020 at 22:08 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 : 823
Unique Edges : 999
Edges With Duplicates : 1859
Total Edges : 2858
Number of Edge Types : 5
Retweet : 637
MentionsInRetweet : 1467
Mentions : 574
Tweet : 163
Replies to : 17
Self-Loops : 180
Reciprocated Vertex Pair Ratio : 0.0334207077326343
Reciprocated Edge Ratio : 0.0646797717184528
Connected Components : 97
Single-Vertex Connected Components : 42
Maximum Vertices in a Connected Component : 459
Maximum Edges in a Connected Component : 2059
Maximum Geodesic Distance (Diameter) : 13
Average Geodesic Distance : 2.503468
Graph Density : 0.00233109536352967
Modularity : 0.409289
NodeXL Version : 1.0.1.433
Data Import : The graph represents a network of 823 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, 18 June 2020 at 01:48 UTC.
The requested start date was Thursday, 18 June 2020 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 13-day, 21-hour, 32-minute period from Thursday, 04 June 2020 at 00:36 UTC to Wednesday, 17 June 2020 at 22:08 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 G2:
[106] nodexl,nodexl_mktng [106] nodexl_mktng,marc_smith [72] marc_smith,smr_foundation [71] enricomolinari,nodexl [71] enricomolinari,bubble [71] bubble,tent [71] tent,lets [71] lets,sleep [70] sleep,comfortably [69] comfortably,under Top Word Pairs in Tweet in G3:
[48] love,#hoteltech [48] #hoteltech,content [41] content,create [31] create,first [29] first,know [29] know,join [29] join,mailing [29] mailing,list [29] list,below [29] #hoteltechnology,#traveltech Top Word Pairs in Tweet in G4:
[12] bchesky,ban [12] ban,discrimination [12] discrimination,airbnb [12] airbnb,many [12] many,years [12] years,ago [12] ago,airbnbcitizen [12] airbnbcitizen,polemic [12] polemic,still [11] downloads,top Top Word Pairs in Tweet in G5:
[6] travel,tourism [6] discussing,state [6] state,travel [6] tourism,olgagomezgarci1 [6] olgagomezgarci1,fmesny [6] #travelscrumhack,#traveltech [6] developers,#traveltech [6] #traveltech,friends [6] friends,online [6] online,#hackathon Top Word Pairs in Tweet in G6:
[11] hospitality,startup [6] tech,enabled [6] enabled,apartment [6] apartment,hotels [6] hotels,custom [5] normal,look [5] look,european [5] european,startups [5] startups,vcs [5] vcs,gave Top Word Pairs in Tweet in G7:
[9] pleasure,speak [9] speak,#tourism [9] #tourism,#travel [9] #travel,#innovation [9] #innovation,today [6] today,18 [6] 18,00 [6] 00,international [6] international,videoconference [6] laurentqueige,pleasure Top Word Pairs in Tweet in G8:
[11] amadeusitgroup,sabre_corp [11] sabre_corp,travelport [11] ai,video [11] video,21 [11] 21,20 [11] 20,20 [11] 20,target [11] target,ndc [11] ndc,feasible [10] feasible,amadeusitgroup Top Word Pairs in Tweet in G9:
[4] madrid,barcelona [4] #demoday,online [3] barcelona,#archipélagonextacelera [2] #archipélagonextacelera,#traveltech [2] programas,madrid [2] conectorspain,#demoday [2] eres,inversor [2] #startups,programas [2] inversor,#startups [2] #startups,hoy Top Word Pairs in Tweet in G10:
[11] people,travel [7] travel,people [7] people,book [7] book,experiences [7] experiences,long [7] long,term [6] term,vision [6] vision,changed [5] changed,100 [5] 100,billion Top Replied-To in Entire Graph:
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Top Replied-To in G4:
Top Replied-To in G5:
Top Mentioned in Entire Graph:
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Top Tweeters in Entire Graph:
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Top Tweeters in G10: