The graph represents a network of 528 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, 31 March 2022 at 02:09 UTC.
The requested start date was Thursday, 31 March 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, 20-hour, 50-minute period from Thursday, 17 March 2022 at 00:55 UTC to Wednesday, 30 March 2022 at 21:46 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 : 528
Unique Edges : 489
Edges With Duplicates : 9834
Total Edges : 10323
Number of Edge Types : 5
Mentions : 2795
Tweet : 346
Retweet : 3918
MentionsInRetweet : 3247
Replies to : 17
Self-Loops : 1714
Reciprocated Vertex Pair Ratio : 0.0502994011976048
Reciprocated Edge Ratio : 0.0957810718358039
Connected Components : 86
Single-Vertex Connected Components : 41
Maximum Vertices in a Connected Component : 300
Maximum Edges in a Connected Component : 9865
Maximum Geodesic Distance (Diameter) : 8
Average Geodesic Distance : 2.831348
Graph Density : 0.00315177390604336
Modularity : 0.076576
NodeXL Version : 1.0.1.449
Data Import : The graph represents a network of 528 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, 31 March 2022 at 02:09 UTC.
The requested start date was Thursday, 31 March 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, 20-hour, 50-minute period from Thursday, 17 March 2022 at 00:55 UTC to Wednesday, 30 March 2022 at 21:46 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:
[4800] #women,#ehealth [4740] #ehealth,#ces2023 [4703] #cx,#women [4204] #ces2023,#finserv [3433] #datascientist,#cloud [1944] #quantum,#des2022 [1800] #cloud,#quantum [1580] #healthtech,#datascientist [1548] chidambara09,#datascientist [1530] #finserv,#fashiontech Top Word Pairs in Tweet in G1:
[4666] #women,#ehealth [4609] #ehealth,#ces2023 [4573] #cx,#women [4078] #ces2023,#finserv [3321] #datascientist,#cloud [1870] #quantum,#des2022 [1727] #cloud,#quantum [1527] #healthtech,#datascientist [1495] chidambara09,#datascientist [1490] #finserv,#fashiontech Top Word Pairs in Tweet in G2:
[117] #women,#ehealth [115] #ehealth,#ces2023 [113] #cx,#women [113] #ces2023,#finserv [101] #datascientist,#cloud [65] #quantum,#des2022 [64] #cloud,#quantum [50] chidambara09,#healthtech [50] #healthtech,#datascientist [47] chidambara09,#datascientist Top Word Pairs in Tweet in G3:
[5] #travel,#traveltech [3] learn,more [3] acomodeo,helps [3] helps,companies [3] companies,find [3] find,serviced [3] serviced,apartments [3] apartments,worldwide [3] worldwide,#travel [3] #digitaltends,#traveltech Top Word Pairs in Tweet in G4:
[19] machine,learning [18] company,pairing [18] pairing,travel [18] travel,advisors [18] advisors,machine [18] learning,leisure [18] leisure,travelers [18] travelers,use [18] use,app [18] app,plan Top Word Pairs in Tweet in G5:
[17] amphibious,bus [17] bus,cheddar [17] cheddar,#autonomousvehicles [17] #autonomousvehicles,#iot [17] #iot,#traveltech [17] #traveltech,cc [17] cc,enricomolinari [17] enricomolinari,jblefevre60 [17] jblefevre60,ym78200 [14] ronald_vanloon,amphibious Top Word Pairs in Tweet in G6:
[5] travel,tech [5] making,easier [4] world,heritage [4] heritage,sites [4] sites,visualised [4] visualised,statistacharts [4] statistacharts,bookingcom [4] bookingcom,believe [4] believe,making [4] easier,everyone Top Word Pairs in Tweet in G7:
[11] article,america [11] america,kevin [11] kevin,jennings [11] jennings,transportation [11] transportation,lead [11] lead,aluenterprise [11] aluenterprise,discusses [11] discusses,benefits [5] benefits,challenges [5] challenges,opportunities Top Word Pairs in Tweet in G8:
[7] iteralix,vitalbook1 [6] tras,iteralix [6] vitalbook1,antonio15814233 [6] antonio15814233,ceo [6] ceo,vyootrip [6] vyootrip,presenta [6] presenta,proyecto [6] proyecto,#traveltech [6] #traveltech,lograr [6] lograr,viajes Top Word Pairs in Tweet in G9:
[7] airline,software [7] software,vendor [7] vendor,dohop [7] dohop,announced [5] announced,undisclosed [5] undisclosed,growth [5] growth,equity [5] equity,round [4] #icemade,airline [4] round,scottish Top Word Pairs in Tweet in G10:
[8] gràcies,aquesta [8] aquesta,acollida [8] acollida,ajlaldea [8] ajlaldea,esperem [8] esperem,l'app [8] l'app,diskover [8] diskover,sigui [8] sigui,complement [8] complement,perfecte [8] perfecte,pels Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
Top Replied-To in G3:
Top Replied-To in G6:
Top Replied-To in G8:
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: