The graph represents a network of 619 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, 19 May 2022 at 01:26 UTC.
The requested start date was Thursday, 19 May 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, 18-hour, 22-minute period from Thursday, 05 May 2022 at 00:48 UTC to Wednesday, 18 May 2022 at 19:10 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 : 619
Unique Edges : 462
Edges With Duplicates : 6119
Total Edges : 6581
Number of Edge Types : 5
Retweet : 2463
MentionsInRetweet : 2289
Mentions : 1614
Replies to : 16
Tweet : 199
Self-Loops : 953
Reciprocated Vertex Pair Ratio : 0.0454545454545455
Reciprocated Edge Ratio : 0.0869565217391304
Connected Components : 94
Single-Vertex Connected Components : 54
Maximum Vertices in a Connected Component : 382
Maximum Edges in a Connected Component : 6220
Maximum Geodesic Distance (Diameter) : 9
Average Geodesic Distance : 3.620417
Graph Density : 0.00210434409816438
Modularity : 0.116044
NodeXL Version : 1.0.1.449
Data Import : The graph represents a network of 619 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, 19 May 2022 at 01:26 UTC.
The requested start date was Thursday, 19 May 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, 18-hour, 22-minute period from Thursday, 05 May 2022 at 00:48 UTC to Wednesday, 18 May 2022 at 19:10 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:
[2228] #cx,#women [2201] #healthtech,#datascientist [2160] #women,#ehealth [2097] #ehealth,#ces2023 [1783] #ai,#digitalhealth [1634] #digitalhealth,#startups [1634] #startups,#cx [1458] chidambara09,#healthtech [1032] #ces2023,#finserv [694] #datascientist,#mwc22 Top Word Pairs in Tweet in G1:
[2177] #cx,#women [2151] #healthtech,#datascientist [2113] #women,#ehealth [2053] #ehealth,#ces2023 [1735] #ai,#digitalhealth [1592] #digitalhealth,#startups [1592] #startups,#cx [1416] chidambara09,#healthtech [1019] #ces2023,#finserv [687] #datascientist,#mwc22 Top Word Pairs in Tweet in G2:
[8] #sustainability,#smartcities [8] #smartcities,glance [8] glance,gigadgets_ [8] gigadgets_,#ehealth [8] #ehealth,#payments [8] #payments,#traveltech [8] #traveltech,labordeolivier [7] enricomolinari,#sustainability [7] labordeolivier,marg [7] veriface,namachain Top Word Pairs in Tweet in G3:
[5] #vacationrentals,#traveltech [4] travel,tech [3] #travel,#traveltech [3] #hospitality,#traveltech [3] #traveltech,#luxury [3] #luxury,#wellness [3] 旅行,traveltech [3] traveltech,トラベルテック [3] トラベルテック,領域のit企業 [3] holiday,rental Top Word Pairs in Tweet in G4:
[9] looking,forward [6] #blockchain,#traveltech [6] traveltech,show [6] first,time [6] time,#ttshow [6] #ttshow,co [6] co,locating [6] locating,btshoweu [6] btshoweu,meetingsshow [6] meetingsshow,meaning Top Word Pairs in Tweet in G5:
[11] attbusiness,#attinfluencer [11] #biomimicry,stem_feed [11] stem_feed,#tech [11] #tech,#aviation [11] #aviation,#designthinking [11] #designthinking,#birding [11] #birding,#traveltech [10] glengilmore,#biomimicry [9] speed,airport [9] airport,check Top Word Pairs in Tweet in G6:
[5] ty,iambriangraham [5] iambriangraham,cc [4] #cx,#iot [3] incredible,#edtech [3] #edtech,#cx [3] #iot,#traveltech [3] #traveltech,#proptech [3] #proptech,floating [3] floating,bridge [3] bridge,ty Top Word Pairs in Tweet in G7:
[45] #cx,#women [44] #healthtech,#datascientist [43] #women,#ehealth [42] #ai,#digitalhealth [41] #ehealth,#ces2023 [39] chidambara09,#healthtech [38] #digitalhealth,#startups [38] #startups,#cx [24] #datascientist,#iot [23] #iot,#ai Top Word Pairs in Tweet in G8:
[23] congrats,valued [23] valued,partner [23] partner,southwestcomms [23] southwestcomms,deployment [23] deployment,300 [23] 300,user [23] user,aluenterprise [23] aluenterprise,oxe [23] oxe,telephony [23] telephony,solution Top Word Pairs in Tweet in G9:
[20] #women,#usa [20] #usa,#insurtech [20] #insurtech,#business [19] #fashionstyle,#fashiontech [18] #fashion,#fashionstyle [17] chidambara09,#fashion [17] #business,#linux [16] #fashionweek,#women [15] #fashiontech,#fashionweek [14] #linux,#flutt Top Word Pairs in Tweet in G10:
[4] learn,more [4] #traveltech,asked [4] asked,well [4] well,one [4] one,picture [4] picture,speak [4] speak,thousand [4] thousand,words [4] words,250 [4] 250,words Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
Top Replied-To in G4:
Top Replied-To in G9:
Top Replied-To in G10:
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: