The graph represents a network of 11,883 Twitter users whose recent tweets contained "SNCF", 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, 13 November 2019 at 17:57 UTC.
The tweets in the network were tweeted over the 1-day, 23-hour, 8-minute period from Monday, 11 November 2019 at 18:22 UTC to Wednesday, 13 November 2019 at 17:31 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 : 11883
Unique Edges : 20150
Edges With Duplicates : 16611
Total Edges : 36761
Self-Loops : 2196
Reciprocated Vertex Pair Ratio : 0.0783496464197068
Reciprocated Edge Ratio : 0.145313992877617
Connected Components : 1139
Single-Vertex Connected Components : 746
Maximum Vertices in a Connected Component : 10011
Maximum Edges in a Connected Component : 34765
Maximum Geodesic Distance (Diameter) : 15
Average Geodesic Distance : 4.395424
Graph Density : 0.000163080808233188
Modularity : 0.508261
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 11,883 Twitter users whose recent tweets contained "SNCF", 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, 13 November 2019 at 17:57 UTC.
The tweets in the network were tweeted over the 1-day, 23-hour, 8-minute period from Monday, 11 November 2019 at 18:22 UTC to Wednesday, 13 November 2019 at 17:31 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 : SNCF
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
Vertex Alpha : Followers
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[3634] c,est [2763] 5,décembre [2650] sncf,ratp [2552] ce,jour [2548] faire,grève [2547] chez,vous [2539] jour,là [2535] décembre,sncf [2532] est,mieux [2530] grève,mais Top Word Pairs in Tweet in G1:
[2523] sncf,ratp [2513] 5,décembre [2513] c,est [2510] jeudi,5 [2510] décembre,sncf [2510] ratp,font [2510] font,grève [2510] grève,mais [2510] mais,sachez [2510] sachez,aussi Top Word Pairs in Tweet in G2:
[195] c,est [130] sncf,groupesncf [120] je,vous [104] pouvez,vous [89] j,ai [87] pour,les [86] je,suis [86] pas,les [82] sur,les [82] groupesncf,sncf Top Word Pairs in Tweet in G3:
[314] c,est [199] je,vous [184] ce,train [173] votre,train [149] 11,19 [148] au,départ [145] sur,les [137] les,trains [136] est,prévu [133] tous,les Top Word Pairs in Tweet in G4:
[214] c,est [176] à,partir [169] #sncf,#ratp [157] et,#manu [157] #manu,tu [138] tu,descends [138] descends,hé [138] hé,pourquoi [138] pourquoi,faire [138] faire,c Top Word Pairs in Tweet in G5:
[63] c,est [47] j,ai [40] sncf,et [33] renfe,sncf [32] viaje,parís [32] parís,2 [32] reto,alta [32] alta,velocidad [32] velocidad,renfe [29] sncf,c Top Word Pairs in Tweet in G6:
[216] à,sncf [114] tu,sais [72] krokodeallll,ratpgroup [69] c,est [68] emilienpetit,krokodeallll [60] pouvez,vous [59] anassekazib,c'est [59] il,faut [57] comment,pouvez [57] c'est,pour Top Word Pairs in Tweet in G7:
[531] renfe,inforenfe [531] inforenfe,renfe_sncf_es [500] renfe_sncf_es,indignatsrenfe [499] indignatsrenfe,renfeindignados [323] ave,barcelona [321] barcelona,malaga [320] mayores,injusticias [320] injusticias,visto [320] barcelona,ave [320] malaga,15 Top Word Pairs in Tweet in G8:
[66] lignej_sncf,bonjour [52] trafic,est [52] votre,train [46] saint,lazare [46] c,est [39] train,est [38] je,vous [36] sur,les [34] votre,service [32] t,il Top Word Pairs in Tweet in G9:
[47] #infotrafic,#rere [44] c,est [44] paris,est [40] j,ai [35] bonne,journée [34] suite,à [30] rere_sncf,bonjour [28] au,départ [28] lignep_sncf,bonjour [25] à,une Top Word Pairs in Tweet in G10:
[33] terhdf,sncf [26] c,est [24] lt,gt [23] à,sncf [21] sncf,terhdf [20] sur,les [19] sur,ligne [17] j,ai [16] mouvement,social [16] des,agents Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
Top Replied-To in G3:
Top Replied-To in G4:
Top Replied-To in G5:
Top Replied-To in G6:
Top Replied-To in G7:
Top Replied-To in G8:
Top Replied-To in G9:
Top Replied-To in G10:
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: