The graph represents a network of 575 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, 20 January 2022 at 03:15 UTC.
The requested start date was Thursday, 20 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 12-day, 10-hour, 5-minute period from Friday, 07 January 2022 at 10:09 UTC to Wednesday, 19 January 2022 at 20:14 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 : 575
Unique Edges : 367
Edges With Duplicates : 15176
Total Edges : 15543
Number of Edge Types : 5
MentionsInRetweet : 5381
Replies to : 8
Mentions : 3811
Retweet : 6125
Tweet : 218
Self-Loops : 1379
Reciprocated Vertex Pair Ratio : 0.0246753246753247
Reciprocated Edge Ratio : 0.0481622306717364
Connected Components : 82
Single-Vertex Connected Components : 43
Maximum Vertices in a Connected Component : 355
Maximum Edges in a Connected Component : 15140
Maximum Geodesic Distance (Diameter) : 10
Average Geodesic Distance : 3.147188
Graph Density : 0.00239054688683533
Modularity : 0.048455
NodeXL Version : 1.0.1.447
Data Import : The graph represents a network of 575 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, 20 January 2022 at 03:15 UTC.
The requested start date was Thursday, 20 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 12-day, 10-hour, 5-minute period from Friday, 07 January 2022 at 10:09 UTC to Wednesday, 19 January 2022 at 20:14 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:
[6043] #women,#ehealth [6039] #cx,#women [6039] #digital,#cx [5982] #datascientist,#digital [5880] #finserv,#fashiontech [5539] #fashiontech,#insurtech [4232] chidambara09,#datascientist [3295] #ces2023,#finserv [3093] #ehealth,#data [3069] #data,#ces2023 Top Word Pairs in Tweet in G1:
[5668] #digital,#cx [5662] #women,#ehealth [5658] #cx,#women [5618] #datascientist,#digital [5512] #finserv,#fashiontech [5189] #fashiontech,#insurtech [3921] chidambara09,#datascientist [3100] #ces2023,#finserv [2910] #ehealth,#data [2889] #data,#ces2023 Top Word Pairs in Tweet in G2:
[3] traveltech,startup [3] travel,tech [3] written,#histotrek [3] #histotrek,read [3] read,full [2] net,senior [2] senior,developer [2] company,barcelona [2] data,feed [2] feed,downloader Top Word Pairs in Tweet in G3:
[334] #cx,#women [334] #women,#ehealth [331] #digital,#cx [328] #datascientist,#digital [327] #finserv,#fashiontech [317] #fashiontech,#insurtech [287] chidambara09,#datascientist [182] #ces2023,#finserv [174] #ehealth,#data [172] #data,#ces2023 Top Word Pairs in Tweet in G4:
[5] much,needed [5] brutal,time [5] time,#travel [5] #travel,industry [5] industry,good [5] good,see [5] see,jlo_said [5] jlo_said,advantagehq [5] advantagehq,pushing [5] pushing,advocating Top Word Pairs in Tweet in G5:
[8] elegidas,reto [8] vyootrip,#viewtravel [7] #startups,elegidas [7] reto,#traveltech [7] #traveltech,vyootrip [7] #viewtravel,proyecto [7] proyecto,inspiravia [7] inspiravia,startups [7] startups,elegidas [6] santalucia_imp,#startups Top Word Pairs in Tweet in G6:
[9] #eddytravels,#ai [9] #ai,#assistant [9] ai,assistant [7] learn,more [7] #assistant,#travel [7] live,webinar [7] discover,increase [7] increase,#travel [7] automate,#support [7] #support,white Top Word Pairs in Tweet in G7:
[2] make,sure Top Word Pairs in Tweet in G8:
[5] ça,rewind_stories [5] rewind_stories,lève [5] lève,700 [5] 700,auprès [5] auprès,kimaventures [5] kimaventures,business [5] business,angels [5] angels,démocratiser [5] démocratiser,ses [5] ses,self Top Word Pairs in Tweet in G9:
[10] #travel,#traveltech [7] massive,airplanes [7] airplanes,take [7] take,stay [7] stay,midair [7] midair,#airtravel [7] #airtravel,#aviation [7] #aviation,#travel [6] travelesquire,massive [5] 13,unusual Top Word Pairs in Tweet in G10:
[33] #cx,#women [33] #women,#ehealth [31] #digital,#cx [30] #datascientist,#digital [30] #finserv,#fashiontech [27] #fashiontech,#insurtech [24] chidambara09,#datascientist [21] #ehealth,#datascience [20] #datascience,#ai [20] #ai,#finserv Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G3:
Top Replied-To in G4:
Top Replied-To in G6:
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:
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Top Tweeters in G5:
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Top Tweeters in G9:
Top Tweeters in G10: