The graph represents a network of 1,417 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, 07 September 2022 at 12:50 UTC.
The requested start date was Wednesday, 07 September 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 9-day, 16-hour, 19-minute period from Sunday, 28 August 2022 at 04:54 UTC to Tuesday, 06 September 2022 at 21:13 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 : 1417
Unique Edges : 1466
Edges With Duplicates : 14716
Total Edges : 16182
Number of Edge Types : 5
Retweet : 5885
MentionsInRetweet : 6976
Tweet : 717
Mentions : 2556
Replies to : 48
Self-Loops : 1821
Reciprocated Vertex Pair Ratio : 0.0337317397078353
Reciprocated Edge Ratio : 0.065262076053443
Connected Components : 50
Single-Vertex Connected Components : 33
Maximum Vertices in a Connected Component : 1343
Maximum Edges in a Connected Component : 16090
Maximum Geodesic Distance (Diameter) : 7
Average Geodesic Distance : 3.359875
Graph Density : 0.00193972305619017
Modularity : 0.153191
NodeXL Version : 1.0.1.504
Data Import : The graph represents a network of 1,417 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, 07 September 2022 at 12:50 UTC.
The requested start date was Wednesday, 07 September 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 9-day, 16-hour, 19-minute period from Sunday, 28 August 2022 at 04:54 UTC to Tuesday, 06 September 2022 at 21:13 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:
[2698] #healthtech,#datascientist [2698] #datascientist,#csuite [2698] #csuite,#digitalhealth [2679] #cx,#ehealth [2679] #ehealth,#finserv [2672] #digitalhealth,#web3 [2666] #finserv,#cloud [2661] #web3,#cx [2408] #cloud,#insurtech [2336] #ai,#iot Top Word Pairs in Tweet in G1:
[403] #ai,#iot [294] #iot,#iiot [268] #iiot,#cx [214] #selfdrivingcars,#fashiontech [203] #datascientist,#csuite [203] #csuite,#digitalhealth [203] #cx,#ehealth [203] #ehealth,#finserv [202] #healthtech,#datascientist [202] #digitalhealth,#web3 Top Word Pairs in Tweet in G2:
[297] #datascience,#bigdata [295] #ai,#ml [295] #ml,#iot [295] #iot,#datascience [295] #bigdata,#analytics [294] #analytics,#serverless [294] #serverless,#linux [294] #linux,#rstats [289] skills,required [288] required,different Top Word Pairs in Tweet in G3:
[2259] #healthtech,#datascientist [2258] #datascientist,#csuite [2258] #csuite,#digitalhealth [2239] #cx,#ehealth [2239] #ehealth,#finserv [2236] #digitalhealth,#web3 [2230] #finserv,#cloud [2225] #web3,#cx [1975] #cloud,#insurtech [1310] #ai,#iot Top Word Pairs in Tweet in G4:
[254] #ai,#selfdrivingcars [221] #healthtech,#datascientist [221] #datascientist,#csuite [221] #csuite,#digitalhealth [221] #cx,#ehealth [221] #ehealth,#finserv [219] #finserv,#cloud [219] #digitalhealth,#web3 [219] #web3,#cx [217] #cloud,#insurtech Top Word Pairs in Tweet in G5:
[240] #ai,#iot [237] #iot,#iiot [221] #iiot,#cx [188] #cx,#ml [174] #selfdrivingcars,#fashiontech [167] #ml,#selfdrivingcars [159] #fashiontech,#smartcity [88] #datascience,#bigdata [87] #smartcity,#autonomousvehicles [83] #bigdata,#analytics Top Word Pairs in Tweet in G6:
[100] #ai,#iot [98] #iot,#iiot [97] #iiot,#cx [95] #cx,#ml [95] #ml,#selfdrivingcars [95] #selfdrivingcars,#fashiontech [95] #fashiontech,#smartcity [88] data,visualization [87] quick,reference [87] reference,data Top Word Pairs in Tweet in G7:
[42] #ai,#artificialintelligence [29] #transport,#selfdrivingcars [29] amazing,#autonomous [29] #autonomous,ebike [29] ebike,startupselfieco [29] startupselfieco,#ai [29] #artificialintelligence,#automation [28] #automation,#transport [26] ronald_vanloon,amazing [24] #selfdrivingcars,#aut Top Word Pairs in Tweet in G8:
[13] self,driving [8] driving,cars [3] स,ल [3] possible,sale [3] sale,apple [3] article,gradient [3] gradient,explain [3] explain,self [3] cars,actually [3] actually,less Top Word Pairs in Tweet in G9:
[28] skills,required [28] required,different [28] different,sectors [28] sectors,#ai [28] #ai,#ml [28] #ml,#iot [28] #iot,#datascience [28] #datascience,#bigdata [28] #bigdata,#analytics [28] #analytics,#serverless Top Word Pairs in Tweet in G10:
[44] #electriccars,#cars [43] #cars,#smartcars [36] #smartcars,#selfdrivingcars [27] #selfdrivingcars,#rides [22] #rides,#whips [14] #whips,#futurecars [14] #futurecars,#speed [8] #electriccars,#future [7] #future,#futureatfullspeed [6] #smartcars,#selfdr Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G3:
Top Replied-To in G4:
Top Replied-To in G8:
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: