The graph represents a network of 3,509 Twitter users whose tweets in the requested range contained "govtech", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Tuesday, 12 November 2019 at 07:03 UTC.
The requested start date was Monday, 11 November 2019 at 01:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 12-day, 2-hour, 51-minute period from Tuesday, 29 October 2019 at 22:03 UTC to Monday, 11 November 2019 at 00:54 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 : 3509
Unique Edges : 4366
Edges With Duplicates : 3165
Total Edges : 7531
Number of Edge Types : 3
Tweet : 1306
Mentions : 6119
Replies to : 106
Self-Loops : 1306
Reciprocated Vertex Pair Ratio : 0.0437222352115969
Reciprocated Edge Ratio : 0.0837813620071685
Connected Components : 650
Single-Vertex Connected Components : 399
Maximum Vertices in a Connected Component : 2161
Maximum Edges in a Connected Component : 5638
Maximum Geodesic Distance (Diameter) : 16
Average Geodesic Distance : 6.148421
Graph Density : 0.000362644615101159
Modularity : 0.567405
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 3,509 Twitter users whose tweets in the requested range contained "govtech", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Tuesday, 12 November 2019 at 07:03 UTC.
The requested start date was Monday, 11 November 2019 at 01:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 12-day, 2-hour, 51-minute period from Tuesday, 29 October 2019 at 22:03 UTC to Monday, 11 November 2019 at 00:54 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 : govtech
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
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[904] à,à [491] â,â [228] georgia's,knowink [228] knowink,electronic [228] electronic,pollbooks [228] pollbooks,used [228] used,check [228] check,voters [228] voters,polls [228] polls,confirm Top Word Pairs in Tweet in G1:
[58] à,à [39] î,î [37] ã,ã [21] government,technology [18] govtech,summit [18] î,ï [16] ï,î [14] u,s [11] action,publique [11] new,bill Top Word Pairs in Tweet in G2:
[164] #govtech,#stateandlocal [33] #security,#govtech [26] #publicsafety,#govtech [18] local,governments [17] #futurestructure,#govtech [16] north,dakota [16] building,free [16] free,innovation [16] innovation,wiki [15] govtechnews,#cdwsocial Top Word Pairs in Tweet in G3:
[228] georgia's,knowink [228] knowink,electronic [228] electronic,pollbooks [228] pollbooks,used [228] used,check [228] check,voters [228] voters,polls [228] polls,confirm [228] confirm,voter [228] voter,registrations Top Word Pairs in Tweet in G4:
[57] ðÿ,ðÿ [51] 14,novembre [46] sommet,des [36] des,govtech [23] lâ,ambition [22] au,sommet [21] les,services [21] des,#startups [20] services,publics [19] ã,paris Top Word Pairs in Tweet in G5:
[192] #govtech,ukauthority [124] #govtech,diginomica [108] #ukgovtech,community [108] community,news [56] #govtech,#security [41] #govtech,publictech [32] #govtech,govcomputing [32] govtechcloud,#ukgovtech [30] diginomica,diginomica_gov [23] #gdpr,#govtech Top Word Pairs in Tweet in G6:
[457] â,â [66] #bigdata,#datascience [53] ht,kirkdborne [39] boozallen,govloop [35] boozallen,#ai [33] boozallen,getmodzy [33] getmodzy,team [32] primer,robotic [32] robotic,process [32] process,automation Top Word Pairs in Tweet in G7:
[28] asociaciones,pãºblico [27] â,quã [23] reglamentaciã,n [22] uno,primeros [22] primeros,temas [22] temas,nos [22] nos,ocupamos [22] ocupamos,consejerã [22] consejerã,fue [22] fue,reglamentaciã Top Word Pairs in Tweet in G8:
[86] strong,message [86] message,world [86] world,honesty [86] honesty,creates [86] creates,wealth [86] wealth,corruption [86] corruption,creates [86] creates,poverty [86] poverty,bitcoin [86] bitcoin,blockchain Top Word Pairs in Tweet in G9:
[21] public,safety [18] #iaem,#nema [11] #fema,#iaem [11] #nema,#dhs [9] #dhs,#disasters [7] #disasters,#emergencymanagement [7] microsoft,ceo [7] ceo,satya [7] satya,nadella [7] nadella,describes Top Word Pairs in Tweet in G10:
[19] #govtech,#civictech [12] now,accepting [12] accepting,applications [12] applications,new [12] new,group [12] group,#stir [12] #stir,projects [12] projects,read [12] read,more [11] #stir,#govtech Top Replied-To in Entire Graph:
Top Replied-To in G2:
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Top Replied-To in G9:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Tweeters in Entire Graph:
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Top Tweeters in G10: