The graph represents a network of 3,133 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, 16 December 2019 at 07:09 UTC.
The requested start date was Monday, 16 December 2019 at 01:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 12-day, 10-hour, 17-minute period from Monday, 02 December 2019 at 01:08 UTC to Saturday, 14 December 2019 at 11:26 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 : 3133
Unique Edges : 3669
Edges With Duplicates : 2996
Total Edges : 6665
Number of Edge Types : 3
Tweet : 1467
Mentions : 5094
Replies to : 104
Self-Loops : 1467
Reciprocated Vertex Pair Ratio : 0.0446479679450487
Reciprocated Edge Ratio : 0.0854794520547945
Connected Components : 702
Single-Vertex Connected Components : 471
Maximum Vertices in a Connected Component : 1750
Maximum Edges in a Connected Component : 4977
Maximum Geodesic Distance (Diameter) : 17
Average Geodesic Distance : 5.170896
Graph Density : 0.000371972399444141
Modularity : 0.526399
NodeXL Version : 1.0.1.422
Data Import : The graph represents a network of 3,133 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, 16 December 2019 at 07:09 UTC.
The requested start date was Monday, 16 December 2019 at 01:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 12-day, 10-hour, 17-minute period from Monday, 02 December 2019 at 01:08 UTC to Saturday, 14 December 2019 at 11:26 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:
[203] #govtech,#stateandlocal [127] #govtech,diginomica [124] #govtech,ukauthority [104] #ukgovtech,community [104] community,news [90] game,changer [76] #civictech,#govtech [74] learn,more [73] technology,game [65] #cybersecurity,#fintech Top Word Pairs in Tweet in G1:
[39] government,technology [28] game,changer [27] technology,game [22] blockchain,technology [21] minority,broadband [21] broadband,initiative [21] initiative,aims [21] aims,connect [21] connect,rural [21] rural,america Top Word Pairs in Tweet in G2:
[183] #govtech,#stateandlocal [31] #security,#govtech [29] learn,more [25] meet,#govtech100 [18] #publicsafety,#govtech [15] govtechnews,meet [13] digital,government [11] join,webcast [11] webcast,12 [11] 12,10 Top Word Pairs in Tweet in G3:
[65] #cybersecurity,#fintech [61] #fintech,#legaltech [59] #legaltech,#healthtech [58] #healthtech,#bugbounty [55] #gdpr,#govtech [42] voting,machines [40] #bugbounty,#ciso [39] #ciso,#gdpr [39] assessing,voting [39] machines,senate Top Word Pairs in Tweet in G4:
[17] latest,report [17] report,'govtech [16] 'govtech,france' [16] tech,help [16] help,governments [16] governments,fight [15] #govtech,market [15] fight,#corruption [15] #civictech,#govtech [14] carlos_santiso,#govtech Top Word Pairs in Tweet in G5:
[14] public,sector [13] #bigdata,#datascience [13] #dataanalytics,#ai [13] positioning,navigation [13] navigation,timing [13] timing,pnt [12] #geospatial,#dataanalytics [12] #ai,scale [12] scale,public [12] sector,databricks Top Word Pairs in Tweet in G6:
[11] austin,tx [11] tx,change [11] change,code [11] code,expand [11] expand,100 [11] 100,year [11] year,floodplain [10] floodsorg,austin [8] opioid,related [7] data,key Top Word Pairs in Tweet in G7:
[2] thejeffbridges,gretathunberg [2] gretathunberg,harry_styles [2] harry_styles,richardobarry [2] richardobarry,mattbellassai [2] mattbellassai,17blackstyies [2] 17blackstyies,lightyear_cars [2] xrbarcelona,xrmallorca [2] xrmallorca,endesa [2] endesa,rebextgramenet [2] rebextgramenet,revoprosost Top Word Pairs in Tweet in G8:
[126] #govtech,diginomica [124] #govtech,ukauthority [103] #ukgovtech,community [103] community,news [55] #govtech,#security [50] #govtech,govcomputing [35] diginomica,diginomica_gov [27] #govtech,publictech [24] platform,#govtech [24] #govtech,#cloud Top Word Pairs in Tweet in G9:
[34] #cio,#cto [22] #cto,#gio [21] blog,'#dashboards [21] '#dashboards,#arcgis' [21] #arcgis',showing [21] showing,many [21] many,#opsdashboard [21] #opsdashboard,examples [21] examples,#dataviz [21] #dataviz,#cio Top Word Pairs in Tweet in G10:
[49] two,articles [49] articles,pinned [49] pinned,lot [49] lot,research [49] research,over [49] over,past [49] past,few [49] few,years [49] years,first [49] first,politico Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Replied-To in G9:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Tweeters in Entire Graph:
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Top Tweeters in G10: