The graph represents a network of 1,565 Twitter users whose tweets in the requested range contained "#selfdrivingcars", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 16 February 2022 at 13:45 UTC.
The requested start date was Wednesday, 16 February 2022 at 01:01 UTC and the maximum number of tweets (going backward in time) was 7,500.
The tweets in the network were tweeted over the 13-day, 15-hour, 41-minute period from Wednesday, 02 February 2022 at 08:22 UTC to Wednesday, 16 February 2022 at 00:04 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 : 1565
Unique Edges : 2166
Edges With Duplicates : 16055
Total Edges : 18221
Number of Edge Types : 5
Tweet : 722
Retweet : 6404
MentionsInRetweet : 9568
Mentions : 1468
Replies to : 59
Self-Loops : 1003
Reciprocated Vertex Pair Ratio : 0.0321322010557723
Reciprocated Edge Ratio : 0.0622637313764732
Connected Components : 141
Single-Vertex Connected Components : 97
Maximum Vertices in a Connected Component : 1324
Maximum Edges in a Connected Component : 17892
Maximum Geodesic Distance (Diameter) : 8
Average Geodesic Distance : 3.337903
Graph Density : 0.00183726497961318
Modularity : 0.157658
NodeXL Version : 1.0.1.449
Data Import : The graph represents a network of 1,565 Twitter users whose tweets in the requested range contained "#selfdrivingcars", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 16 February 2022 at 13:45 UTC.
The requested start date was Wednesday, 16 February 2022 at 01:01 UTC and the maximum number of tweets (going backward in time) was 7,500.
The tweets in the network were tweeted over the 13-day, 15-hour, 41-minute period from Wednesday, 02 February 2022 at 08:22 UTC to Wednesday, 16 February 2022 at 00:04 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 : GraphServerTwitterSearch
Graph Term : #selfdrivingcars
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 Entire Graph:
[2612] #datascientist,#bigdata [2600] #ai,#datascientist [2305] #bigdata,#machinelearning [1670] #machinelearning,#analytics [1296] #analytics,#datascience [952] #datascience,#rstats [715] #ai,#transport [704] #transport,#python [703] #python,#coding [654] need,job Top Word Pairs in Tweet in G1:
[941] #datascientist,#bigdata [938] #ai,#datascientist [837] #bigdata,#machinelearning [578] #machinelearning,#analytics [448] #analytics,#datascience [340] #datascience,#rstats [256] #rstats,#javascript [176] #javascript,#python [175] #machinelearning,#selfdrivingcars [165] #python,#serverless Top Word Pairs in Tweet in G2:
[449] #ai,#datascientist [449] #datascientist,#bigdata [387] #bigdata,#machinelearning [315] #ai,#iot [298] #machinelearning,#analytics [297] #iot,#5g [259] #selfdrivingcars,#ai [252] #analytics,#datascience [196] #selfdrivingcars,#iot [186] #5g,#autonomousvehicles Top Word Pairs in Tweet in G3:
[1014] #datascientist,#bigdata [1005] #ai,#datascientist [897] #bigdata,#machinelearning [648] #machinelearning,#analytics [485] #analytics,#datascience [350] #datascience,#rstats [322] #ai,#transport [321] #transport,#python [320] #python,#coding [289] jobpreference,need Top Word Pairs in Tweet in G4:
[164] #machinelearning,#ai [151] #analytics,#machinelearning [146] #datascientist,#bigdata [144] #ai,#datascientist [125] #bigdata,#machinelearning [117] #evs,#selfdrivingcars [108] #rstats,#reactjs [107] #ai,#python [97] #python,#rstats [95] #reactjs,#iot Top Word Pairs in Tweet in G5:
[38] #autonomousvehicles,#selfdrivingcars [38] #selfdrivingcars,#ai [36] urban,transportation [36] transportation,solution [36] solution,insane [36] insane,gigadgets_ [36] gigadgets_,#autonomousvehicles [35] ronald_vanloon,urban [33] #ai,#artificialintell [31] simulators,testing Top Word Pairs in Tweet in G6:
[35] autonomous,car [35] car,companies [35] companies,outpacing [35] attempts,write [35] write,rules [35] rules,road [35] road,insurance [35] insurance,journal [32] outpacing,regulators [32] regulators,attempts Top Word Pairs in Tweet in G7:
[97] #trucking,industry [95] being,highly [95] highly,important [95] important,#trucking [95] industry,dangerous [95] dangerous,drivers [95] drivers,due [95] due,long [95] long,tiresome [95] tiresome,journeys Top Word Pairs in Tweet in G8:
[158] #ai,#transport [157] #transport,#python [157] #python,#coding [154] need,job [154] job,sign [154] sign,middleman [154] middleman,free [154] free,charge [154] charge,#ai [147] #job,#jobs Top Word Pairs in Tweet in G9:
[53] #smartcars,#selfdrivingcars [47] #electriccars,#cars [47] #cars,#smartcars [41] #futurecars,#speed [35] #selfdrivingcars,#rides [35] #rides,#whips [35] #whips,#futurecars [10] #electriccars,#future [10] self,driving [9] #selfdrivingcars,#tesla Top Word Pairs in Tweet in G10:
[25] experiencing,revolution [25] revolution,driverless [25] driverless,technology [25] technology,maybe [25] maybe,near [25] near,future [25] future,vehicles [25] vehicles,road [24] ai_mogo,experiencing [22] road,comp Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
Top Replied-To in G3:
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Top Replied-To in G7:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
Top Mentioned in G2:
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Top Tweeters in Entire Graph:
Top Tweeters in G1:
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Top Tweeters in G5:
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Top Tweeters in G8:
Top Tweeters in G9:
Top Tweeters in G10: