The graph represents a network of 1,277 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, 12 October 2022 at 12:40 UTC.
The requested start date was Wednesday, 12 October 2022 at 00:01 UTC and the maximum number of tweets (going backward in time) was 7,500.
The tweets in the network were tweeted over the 10-day, 14-hour, 54-minute period from Saturday, 01 October 2022 at 08:17 UTC to Tuesday, 11 October 2022 at 23:12 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 : 1277
Unique Edges : 1239
Edges With Duplicates : 15771
Total Edges : 17010
Number of Edge Types : 5
Retweet : 6035
MentionsInRetweet : 7264
Mentions : 3025
Tweet : 677
Replies to : 9
Self-Loops : 1709
Reciprocated Vertex Pair Ratio : 0.0349127182044888
Reciprocated Edge Ratio : 0.0674698795180723
Connected Components : 168
Single-Vertex Connected Components : 150
Maximum Vertices in a Connected Component : 1078
Maximum Edges in a Connected Component : 16794
Maximum Geodesic Distance (Diameter) : 8
Average Geodesic Distance : 3.193547
Graph Density : 0.00203749481420748
Modularity : 0.144311
NodeXL Version : 1.0.1.506
Data Import : The graph represents a network of 1,277 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, 12 October 2022 at 12:40 UTC.
The requested start date was Wednesday, 12 October 2022 at 00:01 UTC and the maximum number of tweets (going backward in time) was 7,500.
The tweets in the network were tweeted over the 10-day, 14-hour, 54-minute period from Saturday, 01 October 2022 at 08:17 UTC to Tuesday, 11 October 2022 at 23:12 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:
[2746] #iot,#iiot [2460] #machinelearning,#iot [2307] #ai,#machinelearning [2102] #datascientist,#csuite [2099] #healthtech,#datascientist [2099] #cx,#ehealth [2099] #csuite,#digitalhealth [2097] #ehealth,#finserv [2080] #finserv,#cloud [2013] #cx,#selfdrivingcars Top Word Pairs in Tweet in G1:
[1984] #machinelearning,#iot [1889] #ai,#machinelearning [1665] #cx,#selfdrivingcars [1610] #selfdrivingcars,#smartcity [1610] #iot,#iiot [1474] #iiot,#cx [1280] #smartcity,#autonomousvehicles [887] #autonomousvehicles,#datascience [551] #datascience,#bigdata [406] data,#ai Top Word Pairs in Tweet in G2:
[343] #machinelearning,#iot [319] #ai,#machinelearning [276] #iot,#iiot [273] #cx,#selfdrivingcars [258] #selfdrivingcars,#smartcity [250] #iiot,#cx [248] #selfdrivingcars,#ai [242] #ai,#iot [228] akwyz,glengilmore [215] glengilmore,fisheyeboxindia Top Word Pairs in Tweet in G3:
[102] san,francisco [102] autonomous,vehicles [101] vehicles,going [101] several,cruise [101] growing,pains [101] going,growing [100] pains,san [100] residents,know [100] know,well [100] well,several Top Word Pairs in Tweet in G4:
[1783] #datascientist,#csuite [1781] #healthtech,#datascientist [1781] #csuite,#digitalhealth [1781] #cx,#ehealth [1780] #ehealth,#finserv [1769] #finserv,#cloud [1566] #web3,#cx [1566] #digitalhealth,#web3 [1166] #cloud,#insurtech [857] chidambara09,#healthtech Top Word Pairs in Tweet in G5:
[272] #healthtech,#datascientist [272] #csuite,#digitalhealth [272] #datascientist,#csuite [272] #cx,#ehealth [271] #ehealth,#finserv [269] #finserv,#cloud [190] #web3,#cx [190] #digitalhealth,#web3 [187] chidambara09,#healthtech [125] #cloud,#insurtechâ Top Word Pairs in Tweet in G6:
[11] vera,#autonomous [11] intengineering,volvotrucks [11] electric,vehicle [11] goods,intengineering [11] #autonomous,electric [11] volvo's,vera [11] vehicle,#transportation [11] #transportation,goods [10] ronald_vanloon,volvo's [7] #machinelearning,#iot Top Word Pairs in Tweet in G7:
[25] masterai_,#teachers [20] gift,#stem [20] #teachers,imagine [20] imagine,fun [20] #education,#edtech [20] #students,gift [20] #stem,autoautoai [20] fun,#students [20] #teaching,#education [20] autoautoai,#teaching Top Word Pairs in Tweet in G8:
[7] #selfdrivingcars,going [7] #fintech,#insurtech [7] going,nowhere [7] nowhere,#fintech [7] 100,#billion [7] #billion,#selfdrivingcars [7] #insurtech,#insurance [6] spirosmargaris,100 [3] #selfdrivingcars,dojo [3] #insurance,chafkin Top Word Pairs in Tweet in G9:
[8] #ai,#backtothefuture [8] #delorean,#ai [8] delorean,viaja [8] #selfdrivingcars,#delorean [8] #backtothefuture,#drift [8] viaja,#selfdrivingcars [5] encantã,delorean [5] #drift,vã [4] diegocambiaso,encantã [3] diegocambiaso,encantó Top Word Pairs in Tweet in G10:
[7] rs,ruby [7] #lidar,#autonomousvehicles [7] plus,lidar [7] self,driving [7] driving,#lidar [7] guarantee,l4 [7] upgrades,128 [7] lidar,guarantee [7] beam,rs [7] robosense,upgrades Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G4:
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: