The graph represents a network of 638 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, 27 January 2022 at 03:17 UTC.
The requested start date was Thursday, 27 January 2022 at 01:01 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, 31-minute period from Thursday, 13 January 2022 at 01:17 UTC to Wednesday, 26 January 2022 at 20:48 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 : 638
Unique Edges : 490
Edges With Duplicates : 12390
Total Edges : 12880
Number of Edge Types : 5
MentionsInRetweet : 4373
Mentions : 3213
Retweet : 5040
Tweet : 236
Replies to : 18
Self-Loops : 1406
Reciprocated Vertex Pair Ratio : 0.0485327313769752
Reciprocated Edge Ratio : 0.0925726587728741
Connected Components : 106
Single-Vertex Connected Components : 58
Maximum Vertices in a Connected Component : 373
Maximum Edges in a Connected Component : 12427
Maximum Geodesic Distance (Diameter) : 8
Average Geodesic Distance : 2.860583
Graph Density : 0.00228589144845302
Modularity : 0.062793
NodeXL Version : 1.0.1.447
Data Import : The graph represents a network of 638 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, 27 January 2022 at 03:17 UTC.
The requested start date was Thursday, 27 January 2022 at 01:01 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, 31-minute period from Thursday, 13 January 2022 at 01:17 UTC to Wednesday, 26 January 2022 at 20:48 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:
[5201] #cx,#women [5199] #women,#ehealth [4905] #digital,#cx [4889] #finserv,#fashiontech [4883] #datascientist,#digital [4623] #fashiontech,#insurtech [4545] #ces2023,#finserv [4290] #ehealth,#data [4264] #data,#ces2023 [3252] chidambara09,#datascientist Top Word Pairs in Tweet in G1:
[3093] #cx,#women [3092] #women,#ehealth [2936] #finserv,#fashiontech [2930] #digital,#cx [2920] #datascientist,#digital [2796] #fashiontech,#insurtech [2720] #ces2023,#finserv [2565] #ehealth,#data [2553] #data,#ces2023 [1591] chidambara09,#datascientist Top Word Pairs in Tweet in G2:
[2019] #cx,#women [2018] #women,#ehealth [1889] #digital,#cx [1880] #datascientist,#digital [1867] #finserv,#fashiontech [1747] #fashiontech,#insurtech [1746] #ces2023,#finserv [1649] #ehealth,#data [1636] #data,#ces2023 [1584] chidambara09,#datascientist Top Word Pairs in Tweet in G3:
[12] travel,tech [10] madrid,convierte [10] convierte,día [10] día,capital [10] capital,traveltech [8] traveltech,gracias [8] gracias,top [8] top,seeds [8] seeds,lab [8] lab,travel Top Word Pairs in Tweet in G4:
[3] 2022,#traveltech [2] indeed,tricky [2] tricky,focus [2] focus,#payment [2] #payment,side [2] side,things [2] things,try [2] try,fun [2] fun,#traveltech [2] #traveltech,#blockchain Top Word Pairs in Tweet in G5:
[10] #travel,#traveltech [10] making,happen [8] simplicity,ultimate [8] ultimate,sophistication [8] sophistication,travelport [8] travelport,making [8] happen,#traveltech [7] sales,team [7] team,took [7] took,ride Top Word Pairs in Tweet in G6:
[9] elegidas,reto [9] vyootrip,#viewtravel [8] #startups,elegidas [8] reto,#traveltech [8] #traveltech,vyootrip [8] #viewtravel,proyecto [8] proyecto,inspiravia [8] inspiravia,startups [8] startups,elegidas [7] santalucia_imp,#startups Top Word Pairs in Tweet in G7:
[13] #sustainable,flying [13] flying,yacht [13] yacht,mashable [13] mashable,mt [13] mt,ir4_sa [13] ir4_sa,#futureofmobility [13] #futureofmobility,#mobility [13] #mobility,#solarenergy [13] #solarenergy,#traveltech [12] glengilmore,#sustainable Top Word Pairs in Tweet in G8:
[30] #digital,#cx [29] #datascientist,#digital [28] #cx,#women [28] #women,#ehealth [28] #finserv,#fashiontech [25] chidambara09,#datascientist [25] #fashiontech,#insurtech [22] #ces2023,#finserv [20] #ehealth,#data [20] #data,#ces2023 Top Word Pairs in Tweet in G9:
[8] comerços,allotjaments [8] allotjaments,formen [8] formen,part [8] part,d'una [8] d'una,solució [8] solució,diferencial [8] diferencial,capdavantera [8] capdavantera,respecte [8] respecte,aplicacions [8] aplicacions,hi Top Word Pairs in Tweet in G10:
[29] #cx,#women [29] #women,#ehealth [28] #ces2023,#finserv [28] #finserv,#fashiontech [27] #datascientist,#digital [27] #digital,#cx [27] #ehealth,#data [27] #data,#ces2023 [26] chidambara09,#datascientist [26] #fashiontech,#insurtech Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
Top Replied-To in G4:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
Top Mentioned in G2:
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Top Mentioned in G4:
Top Mentioned in G5:
Top Mentioned in G6:
Top Mentioned in G7:
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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:
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Top Tweeters in G9:
Top Tweeters in G10: