The graph represents a network of 3,024 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 2/12/2023 5:00:35 PM. The network was obtained from Twitter on Monday, 13 February 2023 at 01:37 UTC.
The tweets in the network were tweeted over the 2054-day, 0-hour, 48-minute period from Friday, 30 June 2017 at 00:01 UTC to Monday, 13 February 2023 at 00:49 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 : 3024
Unique Edges : 2534
Edges With Duplicates : 7136
Total Edges : 9670
Number of Edge Types : 9
Retweet : 2016
MentionsInRetweet : 3058
Mentions : 1347
Tweet : 2233
Quote : 80
MentionsInQuote : 126
MentionsInReplyTo : 490
Replies to : 318
MentionsInQuoteReply : 2
Self-Loops : 2661
Reciprocated Vertex Pair Ratio : 0.0461354104254044
Reciprocated Edge Ratio : 0.0882016036655212
Connected Components : 894
Single-Vertex Connected Components : 609
Maximum Vertices in a Connected Component : 1247
Maximum Edges in a Connected Component : 6155
Maximum Geodesic Distance (Diameter) : 15
Average Geodesic Distance : 5.296911
Graph Density : 0.000381992029362191
Modularity : 0.377692
NodeXL Version : 1.0.1.510
Data Import : The graph represents a network of 3,024 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 2/12/2023 5:00:35 PM. The network was obtained from Twitter on Monday, 13 February 2023 at 01:37 UTC.
The tweets in the network were tweeted over the 2054-day, 0-hour, 48-minute period from Friday, 30 June 2017 at 00:01 UTC to Monday, 13 February 2023 at 00:49 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:
[479] #insurtech,#finance [440] #finance,#finsevr [402] #finsevr,#ai [357] #ai,#edtech [292] #edtech,#govtech [209] #blockchain,#technology [209] #investing,#banking [208] #govtech,#investing [179] #lunc,#blockchain [178] #banking,#lunc Top Word Pairs in Tweet in G1:
[94] #smartcity,#govtech [94] govts,need [94] #govtech,#ai [94] improve,technology [94] learn,local [94] technology,backbone [94] local,govts [94] backbone,#smartcity [94] need,improve [72] government,technology Top Word Pairs in Tweet in G2:
[457] #insurtech,#finance [422] #finance,#finsevr [387] #finsevr,#ai [343] #ai,#edtech [282] #edtech,#govtech [209] #blockchain,#technology [208] #investing,#banking [205] #govtech,#investing [179] #lunc,#blockchain [178] #banking,#lunc Top Word Pairs in Tweet in G3:
[43] #govtech,#cdwsocial [25] state,local [23] digital,divide [19] ceo,insurance [19] soon,uninsurable [19] december,ceo [19] cyberattacks,soon [19] insurance,company [19] zurich,cyberattacks [19] company,zurich Top Word Pairs in Tweet in G4:
[52] sector,público [50] iberoamérica,ecosistema [50] govtech,iberoamérica [48] ecosistema,actores [48] actores,tecnologías [39] libro,govtech [38] tecnologías,reinventar [38] reinventar,sector [33] policy,brief [31] brief,agendacaf Top Word Pairs in Tweet in G5:
[9] #arcgis,monitor [8] monitor,2023 [6] #location,#intelligence [6] #esri,#arcgis [6] #arcgisenterprise,#arcgisadmin [6] #government,#govtech [5] #government,#location [5] #state,#local [5] #county,#government [5] week,arcgisurban Top Word Pairs in Tweet in G6:
[42] #etgovernment,#government [42] #government,#nationalgovernance [42] #nationalgovernance,#govtech [26] #govtech,#technology [24] national,governance [22] governance,summit [20] more,details [20] summit,2023 [18] details,#etgovernment [16] #etngs,#etgovernment Top Word Pairs in Tweet in G7:
[12] sociedades,públicas [11] bind,govtech [10] focus,world [10] cyber,focus [10] surprising,cyber [10] innovación,abierta [10] world,economic [10] economic,forum [10] sme,connection [9] #data,silos Top Word Pairs in Tweet in G8:
[11] transformation,öffentlichen [10] öffentlichen,sektors [8] sachen,digitale [8] aufgepasst,bist [8] digitale,transformation [8] #govtech,talente [8] shaker,sachen [8] talente,aufgepasst [8] bist,mover [8] stéphanie,schaer Top Word Pairs in Tweet in G9:
[22] #insurtech,#finance [18] #finance,#finsevr [15] #finsevr,#ai [14] #ai,#edtech [10] #edtech,#govtech [7] ai,generated [6] detect,ai [6] federal,funding [5] artificial,intelligence [4] ai,chatbot Top Word Pairs in Tweet in G10:
[24] federal,agencies [24] collaboration,federal [24] economy,america [24] requires,coordination [24] energy,economy [24] lead,requires [24] america,lead [24] coordination,collaboration [23] agencies,sta [23] secgranholm,energy 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 G6:
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: