The graph represents a network of 2,078 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 Monday, 12 December 2022 at 01:41 UTC.
The requested start date was Monday, 12 December 2022 at 01:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 7,500.
The tweets in the network were tweeted over the 12-day, 0-hour, 38-minute period from Monday, 28 November 2022 at 02:47 UTC to Saturday, 10 December 2022 at 03:25 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 : 2078
Unique Edges : 1760
Edges With Duplicates : 4041
Total Edges : 5801
Number of Edge Types : 5
Retweet : 1268
MentionsInRetweet : 2062
Tweet : 1150
Mentions : 1240
Replies to : 81
Self-Loops : 1204
Reciprocated Vertex Pair Ratio : 0.0503685503685504
Reciprocated Edge Ratio : 0.095906432748538
Connected Components : 537
Single-Vertex Connected Components : 333
Maximum Vertices in a Connected Component : 733
Maximum Edges in a Connected Component : 3220
Maximum Geodesic Distance (Diameter) : 15
Average Geodesic Distance : 5.133725
Graph Density : 0.00059429945185433
Modularity : 0.438509
NodeXL Version : 1.0.1.508
Data Import : The graph represents a network of 2,078 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 Monday, 12 December 2022 at 01:41 UTC.
The requested start date was Monday, 12 December 2022 at 01:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 7,500.
The tweets in the network were tweeted over the 12-day, 0-hour, 38-minute period from Monday, 28 November 2022 at 02:47 UTC to Saturday, 10 December 2022 at 03:25 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 : Betweenness Centrality
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[153] ãƒ,ム[100] #fintech,#marketing [92] enricomolinari,#futureofwork [87] top,talent [86] uk,#fintech [86] attract,top [86] #fintech,startup [86] talent,statistacharts [86] startup,attract [83] ciudades,inteligentes Top Word Pairs in Tweet in G1:
[60] ãƒ,ム[53] public,sector [41] government,technology [40] cut,costs [40] agencies,cut [40] aims,develop [40] data,transparency [40] waste,read [40] enable,govt [40] #govtech,#datamanagement Top Word Pairs in Tweet in G2:
[100] #fintech,#marketing [92] enricomolinari,#futureofwork [86] attract,top [86] uk,#fintech [86] talent,statistacharts [86] startup,attract [86] top,talent [86] #fintech,startup [82] #futureofwork,#fintech [82] statistacharts,enricomolinari Top Word Pairs in Tweet in G3:
[38] #govtech,#cdwsocial [25] state,local [25] govtech,#cdwsocial [21] fedtechmagazine,#govtech [18] digital,cities [16] digital,equity [16] social,media [14] cities,survey [14] #digitaltransformation,make [14] #govtech,#civictech Top Word Pairs in Tweet in G4:
[23] #govtech,maturity [23] maturity,index [19] against,corruption [19] govtech,against [17] data,dashboard [15] learn,more [14] 2022,#govtech [13] countries,improving [13] dashboard,live [13] live,learn Top Word Pairs in Tweet in G5:
[36] govtech,campus [34] folge,habt [34] letzte,folge [34] campus,nebensatz [34] nebensatz,bsp [34] habt,block [34] liebe,lagenation [34] lagenation,letzte [34] block,govtech [33] codeforde,liebe Top Word Pairs in Tweet in G6:
[83] ciudades,inteligentes [64] inteligentes,govtech [47] premios,ciudades [32] entrega,premios [24] govtech,2022 [23] reciarg,eamericas [21] 2022,organizado [20] princeconsul,reciarg [20] premio,ciudades [18] govtech,princeconsul Top Word Pairs in Tweet in G8:
[52] digital_jpn,#デジタル監出張報告 [46] govtech,govtechsg [31] 浅沼デジタル監がデジタル政府の先進国シンガポールに出張中です,シンガポールのデジタル庁 [31] govtechsg,などの政府機関を訪問しています [31] singpass,デジタルid [31] 11月28日,30日の三日間 [31] #デジタル監出張報告,11月28日 [31] などの政府機関を訪問しています,singpass [31] シンガポールのデジタル庁,govtech [31] 30日の三日間,浅沼デジタル監がデジタル政府の先進国シンガポールに出張中です Top Word Pairs in Tweet in G9:
[10] flexible,learning [10] models,without [10] losing,campus [10] without,losing [10] demand,flexible [10] campus,culture [10] learning,models [8] nccu,create [8] virtual,homecoming [8] culture,cisco Top Word Pairs in Tweet in G10:
[13] people,first [13] first,design [13] put,people [13] design,deliver [13] deliver,services [13] technology,put [13] govt,expenditure [13] objective,govt [13] expenditure,technology [13] services,benefits Top Replied-To in Entire Graph:
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Top Replied-To in G10:
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: