The graph represents a network of 2,068 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, 19 December 2022 at 01:36 UTC.
The requested start date was Monday, 19 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, 3-minute period from Monday, 05 December 2022 at 01:01 UTC to Sunday, 18 December 2022 at 01:05 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 : 2068
Unique Edges : 1751
Edges With Duplicates : 4316
Total Edges : 6067
Number of Edge Types : 5
Retweet : 1232
MentionsInRetweet : 2096
Mentions : 1427
Tweet : 1235
Replies to : 77
Self-Loops : 1295
Reciprocated Vertex Pair Ratio : 0.0534230312623664
Reciprocated Edge Ratio : 0.101427498121713
Connected Components : 545
Single-Vertex Connected Components : 370
Maximum Vertices in a Connected Component : 920
Maximum Edges in a Connected Component : 4164
Maximum Geodesic Distance (Diameter) : 15
Average Geodesic Distance : 5.825702
Graph Density : 0.000622754737568066
Modularity : 0.42912
NodeXL Version : 1.0.1.508
Data Import : The graph represents a network of 2,068 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, 19 December 2022 at 01:36 UTC.
The requested start date was Monday, 19 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, 3-minute period from Monday, 05 December 2022 at 01:01 UTC to Sunday, 18 December 2022 at 01:05 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:
[135] ãƒ,ム[126] #fintech,#marketing [107] #ces2023,#ces [94] #marketing,#metaverse [85] government,technology [82] reddit,enricomolinari [80] #metaverse,#finserv [80] read,more [68] ciudades,inteligentes [67] more,#govtech Top Word Pairs in Tweet in G1:
[62] ãƒ,ム[57] government,technology [49] read,more [48] more,#govtech [42] last,month [39] aims,develop [39] data,transparency [39] cut,costs [39] machine,readable [39] govt,agencies Top Word Pairs in Tweet in G2:
[125] #fintech,#marketing [107] #ces2023,#ces [93] #marketing,#metaverse [82] reddit,enricomolinari [80] #metaverse,#finserv [58] #ces,#fintech [58] #nfts,reddit [58] value,#nfts [58] enricomolinari,#ces2023 [57] #finserv,#govtech Top Word Pairs in Tweet in G3:
[35] #govtech,#cdwsocial [25] fedtechmagazine,#govtech [25] digital,equity [24] state,local [23] govtech,#cdwsocial [18] agency,shifting [18] #government,services [18] play,agency [18] 2025,plug [18] spent,external Top Word Pairs in Tweet in G4:
[21] #govtech,maturity [21] ecosistema,actores [21] maturity,index [21] reinventar,sector [17] govtechlatam,idb_lab [17] agenda,#govtech [14] 2022,#govtech [13] govtechlatam,tienes [13] tienes,acceso [12] wbg_gov,2022 Top Word Pairs in Tweet in G5:
[13] govtech,campus [10] demo,night [9] krohncaroline,lilithwittmann [9] hab,derweil [9] aufgeschrieben,warum [9] govtechcampusde,hab [9] fuer,fatalen [9] warum,fuer [9] lilithwittmann,honkhase [9] derweil,aufgeschrieben Top Word Pairs in Tweet in G6:
[68] ciudades,inteligentes [48] inteligentes,govtech [32] premios,ciudades [25] entrega,premios [22] reciarg,eamericas [20] princeconsul,reciarg [18] premio,ciudades [18] govtech,2022 [12] 2022,organizado [9] organizado,reciarg Top Word Pairs in Tweet in G7:
[53] upgrading,hvac [53] provide,better [53] know,upgrading [53] article,schools [53] systems,provide [53] better,indoor [53] air,quality [53] schools,know [53] indoor,air [53] hvac,systems Top Word Pairs in Tweet in G8:
[12] reliableinvesto,noahdv84 [12] massumeh18,acinvestorblog [12] heiligenbergnik,reliableinvesto [12] cassiuscuvee,heiligenbergnik [12] teocamelteaux,masecapital [12] masecapital,massumeh18 [12] noahdv84,teocamelteaux [10] investorventure,cassiuscuvee [2] gurgavin,ss [2] low,emission Top Word Pairs in Tweet in G9:
[8] learning,models [7] without,losing [7] flexible,learning [7] campus,culture [7] demand,flexible [7] losing,campus [7] models,without [5] œhybrid,living [5] meetings,faculty [5] culture,cisco Top Word Pairs in Tweet in G10:
[13] people,first [13] design,deliver [13] technology,put [13] put,people [13] objective,govt [13] deliver,services [13] services,benefits [13] expenditure,technology [13] first,design [13] govt,expenditure Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Mentioned in Entire Graph:
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Top Tweeters in Entire Graph:
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Top Tweeters in G10: