The graph represents a network of 497 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 March 2022 at 02:16 UTC.
The requested start date was Thursday, 17 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, 1-hour, 15-minute period from Thursday, 03 March 2022 at 16:57 UTC to Wednesday, 16 March 2022 at 18:12 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 : 497
Unique Edges : 276
Edges With Duplicates : 13454
Total Edges : 13730
Number of Edge Types : 5
Retweet : 5639
MentionsInRetweet : 4147
Mentions : 3811
Replies to : 7
Tweet : 126
Self-Loops : 1826
Reciprocated Vertex Pair Ratio : 0.0507880910683012
Reciprocated Edge Ratio : 0.0966666666666667
Connected Components : 72
Single-Vertex Connected Components : 32
Maximum Vertices in a Connected Component : 316
Maximum Edges in a Connected Component : 13441
Maximum Geodesic Distance (Diameter) : 10
Average Geodesic Distance : 3.336349
Graph Density : 0.00243395859025118
Modularity : 0.039918
NodeXL Version : 1.0.1.449
Data Import : The graph represents a network of 497 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 March 2022 at 02:16 UTC.
The requested start date was Thursday, 17 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, 1-hour, 15-minute period from Thursday, 03 March 2022 at 16:57 UTC to Wednesday, 16 March 2022 at 18:12 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:
[6945] #ces2023,#finserv [6888] #women,#ehealth [6535] #cx,#women [6529] #ehealth,#ces2023 [6490] #datascientist,#cloud [5171] chidambara09,#datascientist [4066] #finserv,#fashiontech [3954] #des2022,#linux [3852] #linux,#cx [3287] #cloud,#digital Top Word Pairs in Tweet in G1:
[4391] #ces2023,#finserv [4362] #women,#ehealth [4139] #cx,#women [4125] #datascientist,#cloud [4119] #ehealth,#ces2023 [2978] #finserv,#fashiontech [2627] chidambara09,#datascientist [2396] #des2022,#linux [2333] #linux,#cx [2061] #cloud,#digital Top Word Pairs in Tweet in G2:
[2546] #ces2023,#finserv [2536] chidambara09,#datascientist [2518] #women,#ehealth [2402] #ehealth,#ces2023 [2388] #cx,#women [2357] #datascientist,#cloud [1550] #des2022,#linux [1511] #linux,#cx [1222] #cloud,#digital [1138] #digital,#des2022 Top Word Pairs in Tweet in G3:
[11] incredible,map [11] map,pangea [11] pangea,modern [11] modern,day [11] day,borders [11] borders,#traveltech [11] #traveltech,#fashiontech [11] #fashiontech,#fintech [11] #fintech,#finserv [9] enricomolinari,incredible Top Word Pairs in Tweet in G4:
[7] tik,tok [7] tok,meets [7] meets,google [7] google,flights [7] flights,traveltech [7] traveltech,startup [7] startup,inspire [7] inspire,book [7] book,next [7] next,vacation Top Word Pairs in Tweet in G5:
[12] traveltech,scotland [8] traveltechscot,fantastic [8] fantastic,write [8] write,traveltech [8] scotland,community [8] community,women [8] women,entrepreneurs [8] entrepreneurs,transforming [8] transforming,#tourism [7] #tourism,#hosp Top Word Pairs in Tweet in G6:
[7] travolution,summit [7] ceo,hiltym [7] chidambara09,#datascientist [7] #datascientist,#cloud [7] #des2022,#linux [7] #linux,#cx [7] #cx,#women [7] #women,#ehealth [7] #ehealth,#ces2023 [7] #ces2023,#finserv Top Word Pairs in Tweet in G7:
[2] 250,000 [2] 000,donate [2] learn,more [2] #travelcrm,#travelagency [2] #travelagency,#travelagencywebsite [2] #travelagencywebsite,traveltech [2] traveltech,taai1951 [2] taai1951,_travtalk_ [2] _travtalk_,grouptvc Top Word Pairs in Tweet in G8:
[6] organisée,par [5] participez,#conférence [5] #conférence,exceptionnelle [5] exceptionnelle,#observatoire [5] #observatoire,#prospective [5] #prospective,funfaircity [5] funfaircity,organisée [5] par,#lab [4] ai,plaisir [4] plaisir,présenter Top Word Pairs in Tweet in G9:
[2] #traveltech,#airtravel [2] united,airlines [2] airlines,longer [2] longer,asks [2] asks,passengers [2] passengers,raise [2] raise,window [2] window,shades [2] shades,takeoff [2] takeoff,landing Top Word Pairs in Tweet in G10:
[7] vols,conèixer [7] conèixer,tendències [7] tendències,sector [7] sector,traveltech [7] traveltech,2022 [7] 2022,parlarem [7] parlarem,aquesta [7] aquesta,jornada [7] jornada,marc [6] turismecat,vols Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G5:
Top Replied-To in G7:
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: