The graph represents a network of 2,186 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, 05 December 2022 at 01:35 UTC.
The requested start date was Monday, 05 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 13-day, 0-hour, 47-minute period from Monday, 21 November 2022 at 02:41 UTC to Sunday, 04 December 2022 at 03:29 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 : 2186
Unique Edges : 1980
Edges With Duplicates : 4530
Total Edges : 6510
Number of Edge Types : 5
Retweet : 1369
MentionsInRetweet : 2506
Tweet : 1094
Mentions : 1450
Replies to : 91
Self-Loops : 1138
Reciprocated Vertex Pair Ratio : 0.0457142857142857
Reciprocated Edge Ratio : 0.087431693989071
Connected Components : 519
Single-Vertex Connected Components : 310
Maximum Vertices in a Connected Component : 867
Maximum Edges in a Connected Component : 4108
Maximum Geodesic Distance (Diameter) : 14
Average Geodesic Distance : 5.070046
Graph Density : 0.000613012702008412
Modularity : 0.440165
NodeXL Version : 1.0.1.508
Data Import : The graph represents a network of 2,186 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, 05 December 2022 at 01:35 UTC.
The requested start date was Monday, 05 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 13-day, 0-hour, 47-minute period from Monday, 21 November 2022 at 02:41 UTC to Sunday, 04 December 2022 at 03:29 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:
[226] maturity,index [184] govtech,maturity [125] #fintech,#marketing [124] index,2022 [105] public,sector [84] #government,agency [71] 2022,uganda [70] #finserv,#fintech [66] #metaverse,#govtech [64] enricomolinari,#futureofwork Top Word Pairs in Tweet in G1:
[56] public,sector [30] government,technology [24] mobile,phishing [24] attacks,2021 [24] phishing,credential [24] credential,theft [24] credential,stealing [24] employees,subject [24] according,lookout's [24] sector,#cybersecurity Top Word Pairs in Tweet in G2:
[119] #fintech,#marketing [70] #finserv,#fintech [66] #metaverse,#govtech [63] #government,agency [58] enricomolinari,#futureofwork [52] #marketing,#metaverse [51] #insurtech,#finserv [50] #marketing,#javascript [49] attract,top [49] #futureofwork,#fintech Top Word Pairs in Tweet in G3:
[37] #govtech,#cdwsocial [17] digital,cities [16] govtech,#cdwsocial [14] cities,survey [14] social,media [14] 2022,digital [14] county,md [14] washington,county [13] public,safety [13] state,local Top Word Pairs in Tweet in G4:
[27] #govtech,maturity [27] maturity,index [22] soluciones,innovadoras [20] startups,soluciones [17] govtech,against [17] against,corruption [16] 2022,#govtech [16] redmatriz,#gobiernoabierto [15] dividends,government [13] #openstate,#govtech Top Word Pairs in Tweet in G5:
[163] maturity,index [154] govtech,maturity [108] index,2022 [71] 2022,uganda [55] nitauganda1,uganda [38] 2020,858 [38] 858,2022 [38] 639,2020 [38] index,value [37] digital,transformation Top Word Pairs in Tweet in G7:
[17] govtech,startups [15] govtech,industry [14] 106,unicorns [14] known,govtech [14] india,106 [14] unicorns,none [14] none,govtech [14] industry,known [14] startups,easygov [13] easygov,india Top Word Pairs in Tweet in G8:
[52] digital_jpn,#デジタル監出張報告 [46] govtech,govtechsg [31] govtechsg,などの政府機関を訪問しています [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 [31] #デジタル監出張報告,11月28日 [31] singpass,デジタルid [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] 11月28日,30日の三日間 [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 Top Word Pairs in Tweet in G9:
[39] govtech,campus [34] habt,block [34] letzte,folge [34] nebensatz,bsp [34] block,govtech [34] campus,nebensatz [34] liebe,lagenation [34] bsp,dafür [34] folge,habt [34] dafür,erwähnt Top Word Pairs in Tweet in G10:
[7] #iaem,#nema [6] #nema,#dhs [5] #disasters,#disasterzone [4] #fema,#iaem [3] #disasterzone,#emergencymanagement [3] #disasterzone,#iaem [2] #hhs,#fema [2] #dhs,#hhs [2] floods,neptanow [2] #disasters,#cisa Top Replied-To in Entire Graph:
Top Replied-To in G3:
Top Replied-To in G4:
Top Replied-To in G5:
Top Replied-To in G6:
Top Replied-To in G7:
Top Replied-To in G9:
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: