The graph represents a network of 4,922 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, 20 July 2022 at 18:26 UTC.
The tweets in the network were tweeted over the 10-day, 2-hour, 42-minute period from Sunday, 10 July 2022 at 15:21 UTC to Wednesday, 20 July 2022 at 18:04 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 : 4922
Unique Edges : 5660
Edges With Duplicates : 1207
Total Edges : 6867
Number of Edge Types : 5
Replies to : 2169
Mentions : 1517
Tweet : 614
Retweet : 1895
MentionsInRetweet : 672
Self-Loops : 667
Reciprocated Vertex Pair Ratio : 0.0186037944372813
Reciprocated Edge Ratio : 0.0365280289330922
Connected Components : 742
Single-Vertex Connected Components : 388
Maximum Vertices in a Connected Component : 3258
Maximum Edges in a Connected Component : 5272
Maximum Geodesic Distance (Diameter) : 20
Average Geodesic Distance : 6.141966
Graph Density : 0.00022831274568908
Modularity : 0.764505
NodeXL Version : 1.0.1.449
Data Import : The graph represents a network of 4,922 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, 20 July 2022 at 18:26 UTC.
The tweets in the network were tweeted over the 10-day, 2-hour, 42-minute period from Sunday, 10 July 2022 at 15:21 UTC to Wednesday, 20 July 2022 at 18:04 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:
[1847] lost,baggage [599] lost,bags [571] baggage,lost [394] lost,luggage [350] luggage,lost [314] pieces,luggage [314] sydney,airport [312] domestic,flights [311] 10,pieces [311] qantas,domestic Top Word Pairs in Tweet in G1:
[199] lost,bags [193] british_airways,baggage [192] baggage,fiasco [192] fiasco,update [192] update,overwhelmed [192] overwhelmed,edi [192] edi,ve [192] ve,hauled [192] hauled,hundreds [192] hundreds,accumulated Top Word Pairs in Tweet in G2:
[117] lost,baggage [52] lost,luggage [50] unclaimed,baggage [46] baggage,store [43] youtuber,unclaimed [39] lost,bags [36] baggage,lost [35] store,bought [35] bought,replacements [35] replacements,items Top Word Pairs in Tweet in G3:
[307] 10,pieces [307] pieces,luggage [307] qantas,domestic [307] domestic,flights [307] flights,sydney [307] sydney,airport [288] company,carrier [288] carrier,outsourced [286] luggage,lost [281] ground,handling Top Word Pairs in Tweet in G4:
[191] lost,baggage [55] baggage,lost [48] klm,lost [41] lost,luggage [25] baggage,claim [24] missing,baggage [22] lost,bags [21] customer,service [18] baggage,reference [17] delayed,baggage Top Word Pairs in Tweet in G5:
[99] lost,baggage [45] baggage,lost [38] lost,luggage [28] aircanada,lost [26] customer,service [21] aircanada,baggage [19] baggage,claim [18] air,canada [17] delayed,baggage [15] lost,office Top Word Pairs in Tweet in G6:
[103] lost,baggage [36] air,france [32] baggage,lost [25] baggage,claim [23] lost,delayed [17] delayed,baggage [17] customer,service [16] file,class [16] class,action [16] action,lawsuit Top Word Pairs in Tweet in G7:
[94] lost,baggage [30] lost,report [27] baggage,lost [24] access,baggage [20] baggage,report [20] delayed,baggage [19] baggage,department [19] baggage,system [18] hear,delayed [18] social,media Top Word Pairs in Tweet in G8:
[86] lost,baggage [40] baggage,lost [18] customer,service [12] urgently,help [12] important,lost [12] baggage,charity [12] charity,group [12] group,ill [12] ill,children [12] children,responding Top Word Pairs in Tweet in G9:
[143] checked,luggage [143] luggage,missing [143] missing,summer [142] piles,lost [142] lost,bags [142] bags,london [142] london,paris [142] paris,toronto [142] toronto,checked [14] baggage,handlers Top Word Pairs in Tweet in G10:
[68] 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 Replied-To in Entire Graph:
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Top Mentioned in Entire Graph:
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Top Tweeters in Entire Graph:
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Top Tweeters in G10: