The graph represents a network of 3,201 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 1/8/2023 5:00:34 PM. The network was obtained from Twitter on Monday, 09 January 2023 at 01:35 UTC.
The tweets in the network were tweeted over the 2000-day, 1-hour, 55-minute period from Tuesday, 18 July 2017 at 22:57 UTC to Monday, 09 January 2023 at 00:53 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 : 3201
Unique Edges : 3138
Edges With Duplicates : 8783
Total Edges : 11921
Number of Edge Types : 9
Tweet : 1941
Retweet : 2234
MentionsInRetweet : 4202
Replies to : 251
MentionsInReplyTo : 812
Mentions : 2202
Quote : 100
MentionsInQuote : 171
MentionsInQuoteReply : 8
Self-Loops : 2322
Reciprocated Vertex Pair Ratio : 0.0453417550191744
Reciprocated Edge Ratio : 0.0867501078981441
Connected Components : 866
Single-Vertex Connected Components : 651
Maximum Vertices in a Connected Component : 1441
Maximum Edges in a Connected Component : 8426
Maximum Geodesic Distance (Diameter) : 11
Average Geodesic Distance : 3.925427
Graph Density : 0.00045239768822243
Modularity : 0.364449
NodeXL Version : 1.0.1.508
Data Import : The graph represents a network of 3,201 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 1/8/2023 5:00:34 PM. The network was obtained from Twitter on Monday, 09 January 2023 at 01:35 UTC.
The tweets in the network were tweeted over the 2000-day, 1-hour, 55-minute period from Tuesday, 18 July 2017 at 22:57 UTC to Monday, 09 January 2023 at 00:53 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:
[379] #ces2023,#ces [287] #ces,#mwc23 [237] #mwc23,#fintech [223] #fintech,#nfts [222] #innovation,#ai [220] #nfts,#innovation [218] #fintech,#marketing [211] #ai,#digital [207] #marketing,#metaverse [206] reddit,enricomolinari Top Word Pairs in Tweet in G1:
[124] public,sector [117] 2023,#govtech [115] watch,2023 [115] derek,manky [115] jim,richberg [114] tune,another [114] richberg,#fortiguardlabs' [114] trends,#cisos [114] fortinetlive,#fortinet's [114] edition,fortinetlive Top Word Pairs in Tweet in G2:
[281] #ces2023,#ces [263] #ces,#mwc23 [231] #mwc23,#fintech [217] #fintech,#nfts [217] #innovation,#ai [214] #nfts,#innovation [202] #ai,#digital [186] ces,#ces [182] future,ces [180] #digital,#coding Top Word Pairs in Tweet in G3:
[117] #government,agency [88] #ces2023,#ces [74] govtechnews,#cdwsocial [72] #govtech,#digitaltransformation [71] read,#blog [59] #govtech,#technology [57] #fintech,#marketing [52] #marketing,#metaverse [52] reddit,enricomolinari [52] #metaverse,#finserv Top Word Pairs in Tweet in G4:
[49] pública,digital [49] transformación,pública [43] digital,latinoamérica [22] libro,transformación [22] presentación,libro [20] latinoamérica,disponible [20] book,transformación [19] luispapagni,diego [19] online,compilado [19] disponible,online Top Word Pairs in Tweet in G5:
[124] years,banking [124] months,govtech [124] hai,twt_kerjamy [124] looking,job [124] banking,months [124] experience,years [124] comms,corporate [124] corporate,experience [124] job,comms [124] twt_kerjamy,looking Top Word Pairs in Tweet in G6:
[77] upgrading,hvac [77] provide,better [77] know,upgrading [77] article,schools [77] systems,provide [77] better,indoor [77] air,quality [77] schools,know [77] indoor,air [77] hvac,systems Top Word Pairs in Tweet in G7:
[57] included,govtech [57] global,recognition [57] strong,focus [57] govtech,leaders [57] fastest,agile [57] recognition,strong [57] focus,digitalization [57] leaders,fastest [57] digitalization,included [56] agile,digit Top Word Pairs in Tweet in G8:
[21] maturity,index [15] #govtech,maturity [14] critical,enhance [14] sector,público [13] index,#gtmi [11] l'impacte,tecnologia [11] llibre,divulgatiu [11] sector,públic [11] millor,l'impacte [11] divulgatiu,entendre Top Word Pairs in Tweet in G9:
[10] tesla,received [9] california,subsidies [8] market,mechanisms [8] mechanisms,2009 [8] subsidies,market [7] indirect,california [7] received,more [7] worth,direct [7] direct,indirect [7] tesla,success Top Word Pairs in Tweet in G10:
[17] #govtech,#fintech [15] hype,cycle [15] gartner,hype [15] digital,government [15] government,2022 [15] #technology,#govtech [15] 2022,gartner [15] cycle,gartner [15] gartner,#technology [13] trends,government 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 G9:
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: