The graph represents a network of 766 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, 25 November 2021 at 03:07 UTC.
The requested start date was Thursday, 25 November 2021 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, 15-hour, 10-minute period from Thursday, 11 November 2021 at 06:26 UTC to Wednesday, 24 November 2021 at 21:37 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 : 766
Unique Edges : 776
Edges With Duplicates : 12215
Total Edges : 12991
Number of Edge Types : 5
Retweet : 5096
MentionsInRetweet : 5565
Mentions : 2026
Tweet : 285
Replies to : 19
Self-Loops : 934
Reciprocated Vertex Pair Ratio : 0.0624012638230648
Reciprocated Edge Ratio : 0.117472118959108
Connected Components : 118
Single-Vertex Connected Components : 76
Maximum Vertices in a Connected Component : 558
Maximum Edges in a Connected Component : 12723
Maximum Geodesic Distance (Diameter) : 9
Average Geodesic Distance : 3.731229
Graph Density : 0.00229526101128006
Modularity : 0.089596
NodeXL Version : 1.0.1.447
Data Import : The graph represents a network of 766 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, 25 November 2021 at 03:07 UTC.
The requested start date was Thursday, 25 November 2021 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, 15-hour, 10-minute period from Thursday, 11 November 2021 at 06:26 UTC to Wednesday, 24 November 2021 at 21:37 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:
[4884] #fashiontech,#ehealth [4385] #women,#datascientist [4075] #ehealth,#datascience [3583] #digital,#science [2983] chidambara09,#digital [2555] #frenchtech,#women [2537] #tech,#fashiontech [2512] #datascience,#finserv [2399] #datascientist,#fashiontech [1967] #datascientist,#tech Top Word Pairs in Tweet in G1:
[4761] #fashiontech,#ehealth [4261] #women,#datascientist [3963] #ehealth,#datascience [3479] #digital,#science [2889] chidambara09,#digital [2500] #tech,#fashiontech [2471] #datascience,#finserv [2449] #frenchtech,#women [2309] #datascientist,#fashiontech [1934] #datascientist,#tech Top Word Pairs in Tweet in G2:
[103] #women,#datascientist [101] #fashiontech,#ehealth [95] #frenchtech,#women [90] #ehealth,#datascience [85] #digital,#science [85] #science,#frenchtech [79] #datascientist,#fashiontech [76] chidambara09,#digital [40] #datascience,#finser [27] #datascience,#finserv Top Word Pairs in Tweet in G3:
[19] phocuswright,conference [13] windingtree,#traveltech [11] well,well [10] co,founder [10] #ehealth,#datascience [10] #fashiontech,#ehealth [9] center,stage [9] #women,#datascientist [8] live,#traveltech [8] travel_ledger,windingtree Top Word Pairs in Tweet in G4:
[27] transport,operators [27] operators,enter [27] enter,digital [27] digital,age [27] age,data [27] data,networks [27] networks,deliver [27] deliver,better [27] better,level [27] level,service Top Word Pairs in Tweet in G5:
[26] traveltech,futures [25] 30,nov [21] futures,anticipating [21] anticipating,shaping [21] shaping,next [21] next,decade [21] decade,travel [19] travel,30 [18] shape,future [16] online,course Top Word Pairs in Tweet in G6:
[12] eddytravels,#ai [11] ai,assistant [10] #eddytravels,#ai [10] #ai,#assistant [8] #ai,assistant [7] futuretravelco,summit [6] eddy,travels [6] travels,ai [6] assistant,available [6] available,travel Top Word Pairs in Tweet in G7:
[12] #digital,#science [12] #women,#datascientist [12] #fashiontech,#ehealth [12] #ehealth,#datascience [11] joshua,ryan [11] ryan,saha [11] chidambara09,#digital [10] #traveltech,#travelindustry [10] traveltech,scotland [9] bcd,alert Top Word Pairs in Tweet in G8:
[10] #traveltech,#aviation [8] augmented,reality [8] reality,airplane [8] airplane,windows [8] windows,concept [8] concept,#innovation [8] #innovation,#gaming [8] #gaming,#gamer [8] #gamer,#gamedev [8] #gamedev,#futuretech Top Word Pairs in Tweet in G9:
[9] sector,turístico [9] experiencias,inmersivas [9] inmersivas,caza [9] caza,turismo [9] turismo,inclusivo [9] inclusivo,#traveltech [9] #traveltech,respuesta [9] respuesta,crisis [9] crisis,sector [8] pleasure,present Top Word Pairs in Tweet in G10:
[21] #insurchallenges,#decesos [21] #decesos,#traveltech [18] pierdas,evento [18] #traveltech,edición [16] inn_somnia,santalucia_imp [15] evento,gratuito [15] gratuito,#insurchallenges [12] javier,moliner [10] santalucia_seg,pierdas [10] edición,santalucia Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G3:
Top Replied-To in G7:
Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Mentioned in G7:
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Top Mentioned in G10:
Top Tweeters in Entire Graph:
Top Tweeters in G1:
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Top Tweeters in G9:
Top Tweeters in G10: