The graph represents a network of 2,824 Twitter users whose recent tweets contained "govtech", or who were replied to, mentioned, retweeted or quoted in those tweets, taken from a data set limited to a maximum of 5,000 tweets, tweeted between 3/26/2006 12:00:00 AM and 2/19/2023 5:00:35 PM. The network was obtained from Twitter on Monday, 20 February 2023 at 01:35 UTC.
The tweets in the network were tweeted over the 1795-day, 11-hour, 12-minute period from Thursday, 22 March 2018 at 13:43 UTC to Monday, 20 February 2023 at 00:56 UTC.
There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, an edge for each "retweet" relationship in a tweet, an edge for each "quote" relationship in a tweet, an edge for each "mention in retweet" relationship in a tweet, an edge for each "mention in reply-to" relationship in a tweet, an edge for each "mention in quote" relationship in a tweet, an edge for each "mention in quote reply-to" relationship in a tweet, and a self-loop edge for each tweet that is not from above.
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 : 2824
Unique Edges : 2847
Edges With Duplicates : 8789
Total Edges : 11636
Number of Edge Types : 9
Retweet : 2312
MentionsInRetweet : 4239
Tweet : 1965
Mentions : 1725
MentionsInQuote : 116
Quote : 77
Replies to : 311
MentionsInReplyTo : 889
MentionsInQuoteReply : 2
Self-Loops : 2436
Reciprocated Vertex Pair Ratio : 0.0616594772900279
Reciprocated Edge Ratio : 0.116156787762906
Connected Components : 735
Single-Vertex Connected Components : 500
Maximum Vertices in a Connected Component : 1264
Maximum Edges in a Connected Component : 8368
Maximum Geodesic Distance (Diameter) : 12
Average Geodesic Distance : 4.772802
Graph Density : 0.000524826922517283
Modularity : 0.348618
NodeXL Version : 1.0.1.510
Data Import : The graph represents a network of 2,824 Twitter users whose recent tweets contained "govtech", or who were replied to, mentioned, retweeted or quoted in those tweets, taken from a data set limited to a maximum of 5,000 tweets, tweeted between 3/26/2006 12:00:00 AM and 2/19/2023 5:00:35 PM. The network was obtained from Twitter on Monday, 20 February 2023 at 01:35 UTC.
The tweets in the network were tweeted over the 1795-day, 11-hour, 12-minute period from Thursday, 22 March 2018 at 13:43 UTC to Monday, 20 February 2023 at 00:56 UTC.
There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, an edge for each "retweet" relationship in a tweet, an edge for each "quote" relationship in a tweet, an edge for each "mention in retweet" relationship in a tweet, an edge for each "mention in reply-to" relationship in a tweet, an edge for each "mention in quote" relationship in a tweet, an edge for each "mention in quote reply-to" relationship in a tweet, and a self-loop edge for each tweet that is not from above.
Layout Algorithm : The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.
Graph Source : TwitterSearch2
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:
[480] #insurtech,#finance [408] #finance,#finsevr [378] #finsevr,#ai [357] #fintech,#finserv [337] #ai,#edtech [275] #edtech,#govtech [219] #blockchain,#technology [213] #investing,#banking [209] #govtech,#investing [188] #lunc,#blockchain Top Word Pairs in Tweet in G1:
[95] #smartcity,#govtech [95] govts,need [95] learn,local [95] technology,backbone [95] local,govts [95] backbone,#smartcity [94] improve,technology [94] need,improve [82] #govtech,#ai [48] today's,digital Top Word Pairs in Tweet in G2:
[355] #fintech,#finserv [161] #marketing,#fintech [157] #finserv,#marketing [141] #insurtech,#finance [123] #ehealth,#fintech [114] statistacharts,enricomolinari [100] #ai,#ehealth [97] #finance,#finsevr [87] #govtech,#metaverse [85] enricomolinari,#ehealth Top Word Pairs in Tweet in G3:
[35] cio,academy [25] ca,cio [24] public,sector [21] digital,equity [21] state,local [18] supreme,court [18] fraud,abuse [18] computer,fraud [18] abuse,act [17] #iaem,#nema Top Word Pairs in Tweet in G4:
[28] govtech,iberoamérica [28] iberoamérica,ecosistema [27] ecosistema,actores [27] actores,tecnologías [26] brief,agendacaf [26] role,#govtech [26] policy,brief [24] latin,america [23] plays,achieving [23] #govtech,plays Top Word Pairs in Tweet in G5:
[316] #insurtech,#finance [292] #finance,#finsevr [276] #finsevr,#ai [260] #ai,#edtech [238] #edtech,#govtech [216] #blockchain,#technology [211] #investing,#banking [202] #govtech,#investing [186] #banking,#lunc [186] #lunc,#blockchain Top Word Pairs in Tweet in G6:
[4] matter,major [4] emergency,plan [4] earthquake,hits [4] those,disabilities [4] turkey,syria [4] hits,california [4] nema_web,usmayors [4] iaem,nema_web [4] california,san [4] major,earthquake Top Word Pairs in Tweet in G7:
[5] buttigieg,25 [5] pete's,smart [5] 25,17 [5] streets,led [5] increased,paramedic [5] always,terrible [5] boy,increased [5] led,death [5] land,navigation [5] smart,streets Top Word Pairs in Tweet in G8:
[11] transformation,öffentlichen [8] #govtech,talente [8] talente,aufgepasst [8] aufgepasst,bist [8] bist,mover [8] sachen,digitale [8] öffentlichen,sektors [8] shaker,sachen [8] mover,shaker [8] digitale,transformation Top Word Pairs in Tweet in G9:
[8] day,solution [8] computers,day [5] quantum,computers [4] 2023,go [4] published,feb [4] copy,gain [4] valuable,#govtech [4] feb,2023 [4] buy,copy [4] being,published Top Word Pairs in Tweet in G10:
[37] #etgovernment,#government [37] #government,#nationalgovernance [37] #nationalgovernance,#govtech [24] #govtech,#technology [21] national,governance [20] governance,summit [19] summit,2023 [17] more,details [16] #etngs,#etgovernment [15] details,#etgovernment Top Replied-To in Entire Graph:
Top Replied-To in G2:
Top Replied-To in G3:
Top Replied-To in G4:
Top Replied-To in G5:
Top Replied-To in G7:
Top Replied-To in G8:
Top Replied-To in G10:
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: