The graph represents a network of 750 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 Friday, 01 November 2019 at 12:49 UTC.
The requested start date was Friday, 01 November 2019 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 13-day, 22-hour, 45-minute period from Friday, 18 October 2019 at 00:09 UTC to Thursday, 31 October 2019 at 22:55 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 : 750
Unique Edges : 801
Edges With Duplicates : 894
Total Edges : 1695
Number of Edge Types : 3
Mentions : 1222
Tweet : 462
Replies to : 11
Self-Loops : 462
Reciprocated Vertex Pair Ratio : 0.0331491712707182
Reciprocated Edge Ratio : 0.0641711229946524
Connected Components : 170
Single-Vertex Connected Components : 82
Maximum Vertices in a Connected Component : 177
Maximum Edges in a Connected Component : 750
Maximum Geodesic Distance (Diameter) : 11
Average Geodesic Distance : 4.314328
Graph Density : 0.00133155318202047
Modularity : 0.458932
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 750 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 Friday, 01 November 2019 at 12:49 UTC.
The requested start date was Friday, 01 November 2019 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 13-day, 22-hour, 45-minute period from Friday, 18 October 2019 at 00:09 UTC to Thursday, 31 October 2019 at 22:55 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 : Followers
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[555] #startup,#traveltech [512] #traveltech,#socialnetworks [420] antibooking,#startup [103] travel,tourism [100] crisis,travel [100] tourism,automated [100] automated,applications [100] applications,cms [100] cms,website [100] website,services Top Word Pairs in Tweet in G1:
[100] crisis,travel [100] travel,tourism [100] tourism,automated [100] automated,applications [100] applications,cms [100] cms,website [100] website,services [100] services,singapore [100] singapore,present [100] present,best Top Word Pairs in Tweet in G2:
[6] find,out [6] wtm,london [5] looking,forward [5] traveltech,startup [5] startup,hotelmize [4] travel,technology [3] forward,meeting [3] kit,use [3] use,travel [3] travel,find Top Word Pairs in Tweet in G3:
[17] travel,industry [6] industry,needs [4] global,distribution [4] distribution,systems [4] people,want [4] thanks,amadeusitgroup [4] amadeusitgroup,travel [4] travel,sellers [4] sellers,now [4] now,access Top Word Pairs in Tweet in G4:
[10] come,learn [10] learn,#5g [10] #5g,transform [9] free,#webinar [9] transform,#travel [9] #travel,#tourism [9] #tourism,#hospitality [8] next,week [8] #hospitality,business [7] wtm_london,next Top Word Pairs in Tweet in G5:
[52] #startup,#traveltech [49] #traveltech,#socialnetworks [45] antibooking,#startup [6] #traveltech,#startup [6] trip,plan [4] fairjungle,gagnante [4] gagnante,concours [4] concours,start [4] start,up [4] up,2019 Top Word Pairs in Tweet in G6:
[31] first,sighting [31] sighting,autonomous [31] autonomous,auto [31] auto,following [31] following,suitcase [31] suitcase,aafs [31] aafs,though [31] though,seemed [31] seemed,much [31] much,drink Top Word Pairs in Tweet in G7:
[503] #startup,#traveltech [463] #traveltech,#socialnetworks [375] antibooking,#startup [51] trip,planner [39] #traveltech,#socialnetwork [38] trip,plan [35] flexible,trip [34] #socialnetworks,#vc [34] #vc,#angelinvesting [34] #angelinvesting,#innovation Top Word Pairs in Tweet in G8:
[28] #video,#stockphotos [28] #stockphotos,#100daysofcode [28] #100daysofcode,#design [28] #design,#uiux [28] #uiux,#url [28] #url,#graphicdesign [28] #graphicdesign,#100daysofcode [28] #100daysofcode,#martech [28] #martech,#webdevelopment [21] #webdevelopment,#qrcode Top Word Pairs in Tweet in G9:
[26] https,t [24] 2019's,biggest [24] biggest,scariest [24] scariest,#security [24] #security,incidents [21] incidents,#databreaches [21] nasty,#php7 [21] #php7,remote [21] remote,code [21] code,execution Top Word Pairs in Tweet in G10:
[12] #travel,#traveltech [10] electric,seaplane [10] seaplane,ale_dubesse [10] ale_dubesse,#travel [9] travelesquire,electric [5] #traveltech,#electricvehicles [5] surfnsunshine,travelesquire [5] thoughts,detachable [5] detachable,airplane [5] airplane,cabin Top Replied-To in Entire Graph:
Top Replied-To in G4:
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:
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Top Tweeters in G5:
Top Tweeters in G6:
Top Tweeters in G7:
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Top Tweeters in G9:
Top Tweeters in G10: