The graph represents a network of 3,674 Twitter users whose recent tweets contained "lost baggage", 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 Wednesday, 27 July 2022 at 11:39 UTC.
The tweets in the network were tweeted over the 10-day, 2-hour, 53-minute period from Sunday, 17 July 2022 at 08:36 UTC to Wednesday, 27 July 2022 at 11:30 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 : 3674
Unique Edges : 3895
Edges With Duplicates : 1352
Total Edges : 5247
Number of Edge Types : 5
Tweet : 558
Replies to : 2070
Mentions : 1659
Retweet : 648
MentionsInRetweet : 312
Self-Loops : 593
Reciprocated Vertex Pair Ratio : 0.0214907508161045
Reciprocated Edge Ratio : 0.0420772303595206
Connected Components : 742
Single-Vertex Connected Components : 383
Maximum Vertices in a Connected Component : 2016
Maximum Edges in a Connected Component : 3639
Maximum Geodesic Distance (Diameter) : 17
Average Geodesic Distance : 4.798532
Graph Density : 0.000278259410688807
Modularity : 0.692346
NodeXL Version : 1.0.1.449
Data Import : The graph represents a network of 3,674 Twitter users whose recent tweets contained "lost baggage", 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 Wednesday, 27 July 2022 at 11:39 UTC.
The tweets in the network were tweeted over the 10-day, 2-hour, 53-minute period from Sunday, 17 July 2022 at 08:36 UTC to Wednesday, 27 July 2022 at 11:30 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 : lost baggage
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 Color : In-Degree
Vertex Radius : In-Degree
Vertex Alpha : In-Degree
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[1198] lost,baggage [372] delayed,baggage [347] lost,luggage [324] lost,delayed [312] baggage,lost [257] baggage,claim [254] help,baggage [243] compensated,delay [239] baggage,compensated [239] delay,drop Top Word Pairs in Tweet in G1:
[254] delayed,baggage [250] lost,delayed [243] compensated,delay [243] help,baggage [239] baggage,compensated [239] delay,drop [239] drop,message [239] law,entitled [239] entitled,2400 [239] 2400,lost Top Word Pairs in Tweet in G2:
[106] lost,baggage [74] lost,luggage [56] unclaimed,baggage [49] baggage,store [48] flight,delays [44] youtuber,unclaimed [38] long,lines [38] delays,cancellations [37] passengers,lost [37] baggage,handlers Top Word Pairs in Tweet in G3:
[99] lost,luggage [92] baggage,claim [86] claim,lost [82] luggage,track [82] track,baggage [81] like,help [81] help,reunite [80] hope,helps [80] hear,like [80] reunite,baggage Top Word Pairs in Tweet in G4:
[85] lost,baggage [29] baggage,lost [17] baggage,claim [11] lost,bags [11] lost,luggage [9] delayed,lost [9] delta,baggage [8] lost,damaged [8] damaged,baggage [8] lost,bag Top Word Pairs in Tweet in G5:
[77] lost,baggage [26] baggage,report [18] lufthansa,lost [17] access,baggage [15] delayed,baggage [14] baggage,tracing [14] baggage,lost [12] customer,service [12] lost,report [11] baggage,claim Top Word Pairs in Tweet in G6:
[73] lost,baggage [30] klm,lost [18] baggage,lost [15] 17,06 [14] lost,bags [11] lost,schiphol [11] baggage,claim [10] schiphol,klm [10] delayed,baggage [9] klm,klm_uk Top Word Pairs in Tweet in G7:
[56] lost,baggage [15] baggage,lost [15] aer,lingus [11] lost,bags [10] dublin,airport [9] fly,tweet [9] tweet,claiming [9] claiming,lost [9] baggage,sky [9] sky,handling Top Word Pairs in Tweet in G8:
[65] lost,baggage [31] june,28 [31] 28,flight [31] flight,tel [31] tel,aviv [31] news,unsustainable [31] unsustainable,urgently [30] aviv,dubrovnik [30] dubrovnik,lost [26] aegeanairlines,june Top Word Pairs in Tweet in G9:
[40] piles,lost [40] lost,bags [40] bags,london [40] london,paris [40] paris,toronto [40] toronto,checked [40] checked,luggage [40] luggage,missing [40] missing,summer [28] 2020,baggage Top Word Pairs in Tweet in G10:
[42] report,lost [42] lost,office [41] baggage,tracing [41] tracing,link [40] lodged,report [39] track,status [39] status,baggage [37] file,reference [37] reference,track [36] kind,sana Top Replied-To in Entire Graph:
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Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Mentioned in G10:
Top Tweeters in Entire Graph:
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Top Tweeters in G10: