The graph represents a network of 705 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, 11 June 2020 at 01:48 UTC.
The requested start date was Thursday, 11 June 2020 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, 21-hour, 8-minute period from Thursday, 28 May 2020 at 01:15 UTC to Wednesday, 10 June 2020 at 22:24 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 : 705
Unique Edges : 884
Edges With Duplicates : 1478
Total Edges : 2362
Number of Edge Types : 5
Tweet : 153
Retweet : 522
MentionsInRetweet : 1264
Mentions : 413
Replies to : 10
Self-Loops : 170
Reciprocated Vertex Pair Ratio : 0.0295678544351782
Reciprocated Edge Ratio : 0.0574374079528719
Connected Components : 101
Single-Vertex Connected Components : 46
Maximum Vertices in a Connected Component : 418
Maximum Edges in a Connected Component : 1837
Maximum Geodesic Distance (Diameter) : 10
Average Geodesic Distance : 2.420856
Graph Density : 0.00273613797549968
Modularity : 0.42797
NodeXL Version : 1.0.1.433
Data Import : The graph represents a network of 705 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, 11 June 2020 at 01:48 UTC.
The requested start date was Thursday, 11 June 2020 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, 21-hour, 8-minute period from Thursday, 28 May 2020 at 01:15 UTC to Wednesday, 10 June 2020 at 22:24 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 G2:
[91] sleek,platform [91] lifts,ty [75] platform,boat [75] boat,lifts [75] chidambara09,enricomolinari [75] intengineering,enricomolinari [75] enricomolinari,intengineering [75] intengineering,worldtrendsinfo [73] worldtrendsinfo,jeroenbartelse [73] jeroenbartelse,drsharwood Top Word Pairs in Tweet in G3:
[22] strategies,engaging [22] engaging,entirely [21] entirely,#mobile [21] #mobile,workforce [21] workforce,#cios [17] #cios,offer [17] aneeshnair,strategies [17] offer,advice [17] advice,#cio [17] #cio,#cto Top Word Pairs in Tweet in G4:
[42] #hoteltechnology,#traveltech [42] love,#hoteltech [42] #hoteltech,content [42] content,create [42] create,first [35] first,know [32] know,join [32] join,mailing [27] mailing,list [27] list,below Top Word Pairs in Tweet in G5:
[14] reinvent,travel [11] june,11 [11] developers,#traveltech [11] #traveltech,friends [11] friends,online [11] online,#hackathon [11] #hackathon,reinvent [11] travel,tourism [11] tourism,industry [11] industry,travelscrum Top Word Pairs in Tweet in G6:
[10] short,term [10] term,rental [6] term,rentals [6] vacation,rentals [6] recovery,program [6] travel,industry [6] cleaning,guidelines [6] social,distancing [6] feel,confident [6] rental,platforms Top Word Pairs in Tweet in G7:
[7] pleasure,speak [4] speak,#tourism [3] #tourism,#travel [2] #travel,#innovation [2] #innovation,today [2] today,18 [2] 18,00 [2] 00,international [2] international,videoconference [2] laurentqueige,pleasure Top Word Pairs in Tweet in G8:
[11] gracias,uriartedavid [11] uriartedavid,equipo [11] equipo,guestpro_com [11] guestpro_com,xpallicer [11] xpallicer,entrevista [11] entrevista,mira [11] mira,futuro [11] futuro,ilusión [11] enriclopezc,gracias [10] ilusión,positivism Top Word Pairs in Tweet in G9:
[3] travel,industry [3] check,industries [3] industries,best [3] best,brightest [3] brightest,saying [3] saying,coronavirus [3] coronavirus,travel [3] windingtree,check [2] industry,#traveltech [2] #ai,transform Top Word Pairs in Tweet in G10:
[10] normal,look [6] look,european [6] european,startups [6] startups,vcs [6] vcs,gave [6] gave,opinion [6] opinion,survey [5] survey,see [5] eu_startups,normal [4] see,predictio Top Replied-To in Entire Graph:
Top Replied-To in G2:
Top Replied-To in G5:
Top Replied-To in G6:
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: