The graph represents a network of 2,606 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 3/12/2023 5:00:36 PM. The network was obtained from Twitter on Monday, 13 March 2023 at 01:34 UTC.
The tweets in the network were tweeted over the 2063-day, 1-hour, 0-minute period from Tuesday, 18 July 2017 at 22:57 UTC to Sunday, 12 March 2023 at 23:57 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 : 2606
Unique Edges : 2698
Edges With Duplicates : 10251
Total Edges : 12949
Number of Edge Types : 9
Retweet : 2592
MentionsInRetweet : 5430
Tweet : 1791
Mentions : 2342
MentionsInReplyTo : 431
Replies to : 212
MentionsInQuote : 72
Quote : 66
MentionsInQuoteReply : 13
Self-Loops : 2258
Reciprocated Vertex Pair Ratio : 0.0561038961038961
Reciprocated Edge Ratio : 0.106246925725529
Connected Components : 638
Single-Vertex Connected Components : 443
Maximum Vertices in a Connected Component : 1372
Maximum Edges in a Connected Component : 10427
Maximum Geodesic Distance (Diameter) : 18
Average Geodesic Distance : 4.943527
Graph Density : 0.000598942643802947
Modularity : 0.29712
NodeXL Version : 1.0.1.510
Data Import : The graph represents a network of 2,606 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 3/12/2023 5:00:36 PM. The network was obtained from Twitter on Monday, 13 March 2023 at 01:34 UTC.
The tweets in the network were tweeted over the 2063-day, 1-hour, 0-minute period from Tuesday, 18 July 2017 at 22:57 UTC to Sunday, 12 March 2023 at 23:57 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:
[573] enricomolinari,#chatgpt [549] #ehealth,#finserv [490] #chatgpt,#marketing [465] #metaverse,gartner_inc [445] gartner_inc,enricomolinari [419] #marketing,#ehealth [404] #insurtech,#finance [367] #finserv,#fintech [339] enricomolinari,#metaverse [330] #finance,#finsevr Top Word Pairs in Tweet in G1:
[566] enricomolinari,#chatgpt [543] #ehealth,#finserv [485] #chatgpt,#marketing [452] #metaverse,gartner_inc [436] gartner_inc,enricomolinari [415] #marketing,#ehealth [363] #finserv,#fintech [333] enricomolinari,#metaverse [247] #marketing,#finserv [237] zhao,enricomolinari Top Word Pairs in Tweet in G2:
[67] government,technology [61] #govtech,#digitaltransformation [54] state,local [53] solution,#govtech [52] state,cio [52] factors,driving [52] priority,year [52] survey,legacy [52] biggest,priority [52] nascio,state Top Word Pairs in Tweet in G3:
[48] digital,equity [32] read,more [25] state,local [19] cloud,services [17] having,moment [17] more,govtechnews [17] moment,happens [16] breaks,down [15] report,read [15] threat,report Top Word Pairs in Tweet in G4:
[16] mobile,government [15] government,help [15] drive,development [15] help,drive [13] mobile,phones [12] wbg_gov,mobile [12] going,#govtech [11] yolamtzm,porruama [11] connect,people [11] innovación,pública Top Word Pairs in Tweet in G5:
[296] #insurtech,#finance [262] #finance,#finsevr [226] #finsevr,#ai [209] #ai,#edtech [203] #edtech,#govtech [183] #govtech,#investing [175] #investing,#banking [173] #banking,#lunc [171] #blockchain,#technology [171] #lunc,#blockchain Top Word Pairs in Tweet in G6:
[16] 2023,virtuellen [16] 08,03 [16] aluenterprise,08 [16] konferenz,egovernment [16] virtuellen,konferenz [16] erleben,aluenterprise [16] egovernment,2023 [16] 03,2023 [14] working,government [14] 2023,vogelitakademie Top Word Pairs in Tweet in G7:
[9] elonmusk,ralphnader [6] ralphnader,elonmusk [4] acquires,github [4] microsoft,acquires [4] github,5b [3] always,terrible [3] investigations,always [3] buttigieg,25 [3] land,navigation [3] terrible,land Top Word Pairs in Tweet in G8:
[2] shellyrkirchoff,skeeduu [2] vickie627,dqschmitt15 [2] silver_strike,ksliberal [2] realkyleewright,natural_femme [2] izmks44,shellyrkirchoff [2] woodcutterbrian,resistenzanow [2] pbunny000,originalgoalie [2] resistenzanow,peregrinepfp [2] ghost_of_tick,fwe1991 [2] vincegottalotta,thereseosulliv2 Top Word Pairs in Tweet in G9:
[39] risk,#databreach [35] #cybersecurity,#fintech [28] #data,silos [26] errors,wastage [25] #business,#govtech [21] #gdpr,#healthtech [21] #dataprotection,#gdpr [20] #cloud,#legaltech [20] #legaltech,#infosec [19] #govtech,#dataprotection Top Word Pairs in Tweet in G10:
[9] 官民の境界線を溶かし,公共 [9] 共同代表に就任しました,官民の境界線を溶かし [9] スタートアップ,大企業 [9] 官公庁,地方自治体など様々な方々とご一緒に [9] 一般社団法人govtech協会を設立し,共同代表に就任しました [9] 行政分野に新しい価値共創モデルを実現する,をミッションに [9] 公共,行政分野に新しい価値共創モデルを実現する [9] をミッションに,スタートアップ [9] 大企業,官公庁 [8] 団体が集まり,一般社団法人govtech協会を設立 Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G3:
Top Replied-To in G4:
Top Replied-To in G6:
Top Replied-To in G7:
Top Replied-To in G8:
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: