The graph represents a network of 596 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 August 2022 at 01:28 UTC.
The requested start date was Thursday, 18 August 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, 19-hour, 33-minute period from Thursday, 04 August 2022 at 01:56 UTC to Wednesday, 17 August 2022 at 21:29 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 : 596
Unique Edges : 472
Edges With Duplicates : 6638
Total Edges : 7110
Number of Edge Types : 5
Retweet : 2666
MentionsInRetweet : 1875
Replies to : 10
Mentions : 2184
Tweet : 375
Self-Loops : 1486
Reciprocated Vertex Pair Ratio : 0.0348258706467662
Reciprocated Edge Ratio : 0.0673076923076923
Connected Components : 99
Single-Vertex Connected Components : 52
Maximum Vertices in a Connected Component : 375
Maximum Edges in a Connected Component : 6701
Maximum Geodesic Distance (Diameter) : 14
Average Geodesic Distance : 3.977756
Graph Density : 0.00234617336867633
Modularity : 0.1048
NodeXL Version : 1.0.1.504
Data Import : The graph represents a network of 596 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 August 2022 at 01:28 UTC.
The requested start date was Thursday, 18 August 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, 19-hour, 33-minute period from Thursday, 04 August 2022 at 01:56 UTC to Wednesday, 17 August 2022 at 21:29 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:
[3091] #healthtech,#datascientist [3083] #ehealth,#finserv [3033] #datascientist,#csuite [3033] #csuite,#digitalhealth [3030] #finserv,#cloud [3028] #cx,#ehealth [3026] #digitalhealth,#web3 [3024] #web3,#cx [2833] #cloud,#insurtech [1958] chidambara09,#healthtech Top Word Pairs in Tweet in G1:
[3054] #healthtech,#datascientist [3046] #ehealth,#finserv [3001] #datascientist,#csuite [3001] #csuite,#digitalhealth [2996] #cx,#ehealth [2996] #finserv,#cloud [2994] #digitalhealth,#web3 [2992] #web3,#cx [2799] #cloud,#insurtech [1922] chidambara09,#healthtech Top Word Pairs in Tweet in G2:
[63] #bigdata,#analytics [44] #women,#usa [40] #python,#flutter [39] #analytics,#ai [37] mission,#mars2030 [37] #mars2030,visualcap [37] visualcap,#tech [37] #tech,#innovation [37] #innovation,#datascience [37] #datascience,#bigdata Top Word Pairs in Tweet in G3:
[8] travel,tech [7] traveltech,firm [6] #accessories,#geek [6] #geek,#supplier [5] low,#battery [5] society,pass [4] #travel,#traveltech [4] digital,age [4] independence,day [4] #supplier,#promotional Top Word Pairs in Tweet in G4:
[17] enricomolinari,senegalese [17] senegalese,island [17] island,fighting [17] fighting,rising [17] rising,seas [17] seas,wef [17] wef,enricomolinari [17] enricomolinari,#traveltech [17] #traveltech,#smartcities [17] #smartcities,#finserv Top Word Pairs in Tweet in G5:
[26] #fashiontech,#fashionweek [25] chidambara09,#fashion [25] #fashionstyle,#fashiontech [25] #fashionweek,#women [25] #women,#usa [25] #usa,#dresses [25] #dresses,#insurtech [24] #fashion,#fashionstyle [24] #insurtech,#business [24] #business,#lin Top Word Pairs in Tweet in G6:
[17] #rt,phocuswire [10] #traveltech,#travelnews [9] read,more [9] #phocuswire,#travelnews [8] more,#phocuswire [8] #travelnews,#traveltech [8] phocuswire,#traveltech [6] hear,latest [6] latest,#phocuswright [6] #travel,market Top Word Pairs in Tweet in G7:
[3] another,major [3] major,roadblock [3] roadblock,return [3] return,normalcy [3] normalcy,prices [3] prices,gas [3] gas,pump [3] pump,soaring [3] soaring,airline [3] airline,tickets Top Word Pairs in Tweet in G8:
[13] head,product [13] product,alexisboshoff [13] alexisboshoff,multiple [13] multiple,time [13] time,founder [13] founder,exited [13] exited,traveltech [13] traveltech,co [13] co,'19 [13] '19,known Top Word Pairs in Tweet in G9:
[10] travel,industry [7] augmented,reality [7] reality,ar [7] ar,metaverse [7] metaverse,transform [7] transform,travel [7] industry,experience [7] experience,improve [7] improve,hospitality [6] hahznft,augmented Top Word Pairs in Tweet in G10:
[18] #women,#usa [12] #fashiontech,#fashionweek [12] #finserv,#python [11] traveltech,firm [11] #fashionweek,#women [10] #healthtech,#datascientist [10] #ehealth,#finserv [9] chidambara09,#healthtech [9] #finserv,#cloud [9] #cloud,#insurtech Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G5:
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: