TAP_AIRLINE, Twitter, 1/9/2020 10:05:27 PM, 219923


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TAP_AIRLINE Twitter NodeXL SNA Map and Report for Thursday, 09 January 2020 at 21:24 UTC
TAP_AIRLINE Twitter NodeXL SNA Map and Report for Thursday, 09 January 2020 at 21:24 UTC
From:
marc_smith
Uploaded on:
January 09, 2020
Short Description:
TAP_AIRLINE via NodeXL http://bit.ly/39Rv8ee
@airline_ratings
@tapairportugal
@flight_refunds
@joellemessianu
@airline
@itsthecatia
@iberia_en
@mp_portugues
@raeox
@jorgecarmo9

Top hashtags:
#airlineschedules
#routes
#tapairportugal
#backinlondon
#travel
#technology

Description:
Description
The graph represents a network of 37 Twitter users whose recent tweets contained "TAP_AIRLINE", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 18,000 tweets. The network was obtained from Twitter on Thursday, 09 January 2020 at 21:24 UTC.

The tweets in the network were tweeted over the 7-day, 7-hour, 28-minute period from Thursday, 02 January 2020 at 05:04 UTC to Thursday, 09 January 2020 at 12:32 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


Overall Graph Metrics
Vertices : 37
Unique Edges : 32
Edges With Duplicates : 0
Total Edges : 32
Number of Edge Types : 5
MentionsInRetweet : 9
Mentions : 8
Replies to : 5
Retweet : 3
Tweet : 7
Self-Loops : 7
Reciprocated Vertex Pair Ratio : 0
Reciprocated Edge Ratio : 0
Connected Components : 14
Single-Vertex Connected Components : 4
Maximum Vertices in a Connected Component : 13
Maximum Edges in a Connected Component : 14
Maximum Geodesic Distance (Diameter) : 4
Average Geodesic Distance : 1.73516
Graph Density : 0.0187687687687688
Modularity : 0.710205
NodeXL Version : 1.0.1.422
Graph Gallery URL : https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=219920
Data Import : The graph represents a network of 37 Twitter users whose recent tweets contained "TAP_AIRLINE", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 18,000 tweets. The network was obtained from Twitter on Thursday, 09 January 2020 at 21:24 UTC.

The tweets in the network were tweeted over the 7-day, 7-hour, 28-minute period from Thursday, 02 January 2020 at 05:04 UTC to Thursday, 09 January 2020 at 12:32 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 : TwitterSearch
Graph Term : TAP_AIRLINE
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 : In-Degree

Top Influencers: Top 10 Vertices, Ranked by Betweenness Centrality
Top URLs
Top URLs in Tweet in Entire Graph:
[2] https://www.cirium.com/thoughtcloud/the-best-airline-schedule-intelligence/?cmpid=SOC|CIR|CIR-2019-tc&sf226217474=1
[2] https://sputniknews.com/society/202001021077923908-chinese-man-who-tossed-coins-into-planes-engine-for-good-luck-ordered-to-pay-airline-17200--/
[1] https://www.mundoportugues.pt/saber-se-a-tap-e-considerada-uma-companhia-segura/
[1] https://semanariov.pt/2020/01/04/tap-portugal-entre-as-companhias-aereas-mais-seguras-do-mundo-diz-airline-ratings/
[1] https://www.airlineratings.com/news/top-twenty-safest-airlines-2020/
[1] https://trib.al/YAjYuU4
[1] https://www.airlineratings.com/news/safest-airlines-in-the-world-qantas-2020/

Top URLs in Tweet in G3:
[1] https://www.airlineratings.com/news/safest-airlines-in-the-world-qantas-2020/
[1] https://semanariov.pt/2020/01/04/tap-portugal-entre-as-companhias-aereas-mais-seguras-do-mundo-diz-airline-ratings/
[1] https://www.mundoportugues.pt/saber-se-a-tap-e-considerada-uma-companhia-segura/

Top URLs in Tweet in G5:
[1] https://www.airlineratings.com/news/top-twenty-safest-airlines-2020/

Top URLs in Tweet in G6:
[2] https://www.cirium.com/thoughtcloud/the-best-airline-schedule-intelligence/?cmpid=SOC|CIR|CIR-2019-tc&sf226217474=1

Top URLs in Tweet in G10:
[2] https://sputniknews.com/society/202001021077923908-chinese-man-who-tossed-coins-into-planes-engine-for-good-luck-ordered-to-pay-airline-17200--/

Top Domains
Top Domains in Tweet in Entire Graph:
[2] cirium.com
[2] airlineratings.com
[2] sputniknews.com
[1] mundoportugues.pt
[1] semanariov.pt
[1] trib.al

Top Domains in Tweet in G3:
[1] airlineratings.com
[1] semanariov.pt
[1] mundoportugues.pt

Top Domains in Tweet in G5:
[1] airlineratings.com

Top Domains in Tweet in G6:
[2] cirium.com

Top Domains in Tweet in G10:
[2] sputniknews.com

Top Hashtags
Top Hashtags in Tweet in Entire Graph:
[1] airlineschedules
[1] routes
[1] tapairportugal
[1] backinlondon
[1] travel
[1] technology
[1] happy2020



Top Hashtags in Tweet in G2:
[1] tapairportugal
[1] happy2020

Top Hashtags in Tweet in G4:
[1] backinlondon
[1] travel
[1] technology

Top Hashtags in Tweet in G6:
[1] airlineschedules
[1] routes

Top Words
Top Words in Tweet in Entire Graph:
[18] Words in Sentiment List#1: Positive
[10] Words in Sentiment List#2: Negative
[0] Words in Sentiment List#3: Angry/Violent
[848] Non-categorized Words
[876] Total Words
[23] tap
[19] airline
[12] mais
[11] 20
[11] seguras

Top Words in Tweet in G1:
[6] seguramente
[6] uma
[6] melhores
[6] notícias
[6] podíamos
[6] receber
[6] início
[6] 2020
[6] acordo
[6] site

Top Words in Tweet in G2:
[5] tap
[4] tapairportugal
[4] flight
[3] airline
[2] airline_ratings
[2] mais
[2] recommends
[2] go
[2] competitor
[2] fix

Top Words in Tweet in G3:
[5] airline
[4] tap
[2] 20
[2] portugal
[2] companhias
[2] mais
[2] seguras
[2] mundo
[2] ratings

Top Words in Tweet in G5:
[4] em
[4] lugar
[2] parabéns
[2] tap
[2] air
[2] portugal
[2] aos
[2] nossos
[2] ex
[2] alunos

Top Words in Tweet in G6:
[4] data
[2] tap
[2] direct
[2] feeds
[2] read
[2] 900
[2] global
[2] airlines
[2] access
[2] 20

Top Words in Tweet in G7:
[2] fly

Top Words in Tweet in G8:
[2] pathetic
[2] service

Top Words in Tweet in G10:
[2] chinese
[2] man
[2] tossed
[2] coins
[2] plane
[2] engine
[2] good
[2] luck
[2] ordered
[2] pay

Top Word Pairs
Top Word Pairs in Tweet in Entire Graph:
[11] mais,seguras
[9] seguras,mundo
[8] airline_ratings,tap
[8] 20,companhias
[8] companhias,aéreas
[8] aéreas,mais
[7] seguramente,uma
[7] uma,melhores
[7] melhores,notícias
[7] notícias,podíamos

Top Word Pairs in Tweet in G1:
[6] seguramente,uma
[6] uma,melhores
[6] melhores,notícias
[6] notícias,podíamos
[6] podíamos,receber
[6] receber,início
[6] início,2020
[6] 2020,acordo
[6] acordo,site
[6] site,airline_ratings

Top Word Pairs in Tweet in G2:
[2] airline_ratings,tap
[2] tapairportugal,airline
[2] airline,recommends
[2] recommends,go
[2] go,competitor
[2] competitor,fix
[2] fix,mistake
[2] mistake,tap
[2] tap,cancelled
[2] cancelled,flight

Top Word Pairs in Tweet in G3:
[2] tap,portugal
[2] mais,seguras
[2] seguras,mundo
[2] airline,ratings

Top Word Pairs in Tweet in G5:
[2] parabéns,tap
[2] tap,air
[2] air,portugal
[2] portugal,aos
[2] aos,nossos
[2] nossos,ex
[2] ex,alunos
[2] alunos,seu
[2] seu,trabalho
[2] trabalho,colocaram

Top Word Pairs in Tweet in G6:
[2] tap,direct
[2] direct,feeds
[2] feeds,read
[2] read,900
[2] 900,global
[2] global,airlines
[2] airlines,access
[2] access,20
[2] 20,years
[2] years,historical

Top Word Pairs in Tweet in G10:
[2] chinese,man
[2] man,tossed
[2] tossed,coins
[2] coins,plane
[2] plane,engine
[2] engine,good
[2] good,luck
[2] luck,ordered
[2] ordered,pay
[2] pay,airline

Top Replied-To
Top Mentioned
Top Tweeters
Top Tweeters in Entire Graph:
@british_airways
@flight_refunds
@bopinion
@tapairportugal
@sputnikint
@iberia_en
@goairlinesindia
@salvador__29
@cat_in_the_tap
@bigdaddykane66

Top Tweeters in G1:
@salvador__29
@azores1963
@embportugal_ca
@jorgecarmo9
@eriwen83
@airline_ratings
@invboeingexpres

Top Tweeters in G2:
@flight_refunds
@tapairportugal
@iberia_en
@joellemessianu
@deniseneves
@fjvelascog

Top Tweeters in G3:
@semanariov
@mp_portugues
@raeox
@apucheglazov

Top Tweeters in G4:
@british_airways
@itsthecatia
@tap_portugal

Top Tweeters in G5:
@alexdbalves
@sevenairacademy
@airline

Top Tweeters in G6:
@shelleyjeffcoat
@cirium

Top Tweeters in G7:
@bigdaddykane66
@caramooney

Top Tweeters in G8:
@goairlinesindia
@_yashmittal_

Top Tweeters in G9:
@aeroplan
@aaronbearce

Top Tweeters in G10:
@sputnikint
@tap_a_dime


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