The graph represents a network of 562 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, 09 June 2022 at 01:31 UTC.
The requested start date was Thursday, 09 June 2022 at 00:01 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 13-day, 16-hour, 38-minute period from Thursday, 26 May 2022 at 01:57 UTC to Wednesday, 08 June 2022 at 18:35 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 : 562
Unique Edges : 411
Edges With Duplicates : 9060
Total Edges : 9471
Number of Edge Types : 5
Tweet : 180
Retweet : 3818
MentionsInRetweet : 3033
Mentions : 2428
Replies to : 12
Self-Loops : 1354
Reciprocated Vertex Pair Ratio : 0.0384615384615385
Reciprocated Edge Ratio : 0.0740740740740741
Connected Components : 113
Single-Vertex Connected Components : 61
Maximum Vertices in a Connected Component : 309
Maximum Edges in a Connected Component : 9077
Maximum Geodesic Distance (Diameter) : 8
Average Geodesic Distance : 2.932789
Graph Density : 0.00222657811102442
Modularity : 0.066472
NodeXL Version : 1.0.1.449
Data Import : The graph represents a network of 562 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, 09 June 2022 at 01:31 UTC.
The requested start date was Thursday, 09 June 2022 at 00:01 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 13-day, 16-hour, 38-minute period from Thursday, 26 May 2022 at 01:57 UTC to Wednesday, 08 June 2022 at 18:35 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:
[3970] #cx,#women [3957] #datascientist,#mwc22 [3927] #women,#ehealth [3875] #mwc22,#ai [3821] #ehealth,#ces2023 [2179] #healthtech,#datascientist [1812] #digitalhealth,#datascientist [1759] #ai,#healthtech [1556] #healthtech,#ml [1547] #iiot,#cx Top Word Pairs in Tweet in G1:
[2672] #cx,#women [2659] #datascientist,#mwc22 [2655] #women,#ehealth [2613] #mwc22,#ai [2594] #ehealth,#ces2023 [1411] #healthtech,#datascientist [1279] #digitalhealth,#datascientist [1246] #ai,#healthtech [1112] #healthtech,#ml [1102] #iiot,#cx Top Word Pairs in Tweet in G2:
[7] travel,recovery [4] travel,tech [4] crm,online [4] online,booking [4] traveltech,show [4] tech,key [4] key,travel [4] recovery,covid [3] business,travel [3] ai,crm Top Word Pairs in Tweet in G3:
[974] #datascientist,#mwc22 [974] #cx,#women [947] #women,#ehealth [941] #mwc22,#ai [907] #ehealth,#ces2023 [584] #healthtech,#datascientist [534] chidambara09,#healthtech [397] #digitalhealth,#datascientist [377] #ai,#healthtech [357] #ces2023,#finâ Top Word Pairs in Tweet in G4:
[323] #datascientist,#mwc22 [323] #cx,#women [323] #women,#ehealth [320] #mwc22,#ai [319] #ehealth,#ces2023 [183] #healthtech,#datascientist [179] chidambara09,#healthtech [144] #ces2023,#fin [135] #digitalhealth,#datascientist [135] #ai,#healthtech Top Word Pairs in Tweet in G5:
[8] travel,tech [6] 29,30 [6] 30,june [6] registration,open [5] delighted,welcome [5] official,media [5] media,partner [5] partner,#ttshow [5] #ttshow,2022 [5] 2022,registration Top Word Pairs in Tweet in G6:
[3] highlighting,work [3] work,whereverly [3] whereverly,combat [3] combat,visitor [3] visitor,management [3] management,scotland [3] scotland,using [3] using,#technology [3] #technology,one [3] one,great Top Word Pairs in Tweet in G7:
[3] consent,#facialrecognition [3] #facialrecognition,sped [3] sped,airport [3] airport,check [3] check,âž [2] travelesquire,airbus [2] airbus,unveiled [2] unveiled,#netzero [2] #netzero,concept [2] concept,mt Top Word Pairs in Tweet in G8:
[10] until,proven [5] today,travelgatex [5] travelgatex,team [5] team,surpassed [5] surpassed,themselves [5] part,event [5] event,taking [5] taking,place [5] œin,silicon [5] silicon,valley Top Word Pairs in Tweet in G10:
[5] week,hundreds [5] hundreds,senior [5] senior,#traveltech [5] #traveltech,executives [5] executives,dublin [5] dublin,attend [5] attend,futuretravelx [5] futuretravelx,summit [5] summit,therds [4] entirl,week Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G3:
Top Replied-To in G4:
Top Replied-To in G5:
Top Replied-To in G6:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
Top Mentioned in G2:
Top Mentioned in G3:
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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:
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Top Tweeters in G7:
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Top Tweeters in G9:
Top Tweeters in G10: