The graph represents a network of 3,290 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, 23 December 2019 at 07:09 UTC.
The requested start date was Monday, 23 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 13-day, 9-hour, 49-minute period from Monday, 09 December 2019 at 01:50 UTC to Sunday, 22 December 2019 at 11:39 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 : 3290
Unique Edges : 3957
Edges With Duplicates : 3138
Total Edges : 7095
Number of Edge Types : 4
Mentions : 2255
MentionsInRetweet : 3249
Tweet : 1496
Replies to : 95
Self-Loops : 1496
Reciprocated Vertex Pair Ratio : 0.0460805084745763
Reciprocated Edge Ratio : 0.0881012658227848
Connected Components : 686
Single-Vertex Connected Components : 468
Maximum Vertices in a Connected Component : 1793
Maximum Edges in a Connected Component : 5163
Maximum Geodesic Distance (Diameter) : 15
Average Geodesic Distance : 5.125093
Graph Density : 0.000365037367812576
Modularity : 0.532386
NodeXL Version : 1.0.1.422
Data Import : The graph represents a network of 3,290 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, 23 December 2019 at 07:09 UTC.
The requested start date was Monday, 23 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 13-day, 9-hour, 49-minute period from Monday, 09 December 2019 at 01:50 UTC to Sunday, 22 December 2019 at 11:39 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:
[197] #govtech,#stateandlocal [154] predictions,2020 [151] top,20 [127] security,predictions [124] 20,security [113] #govtech,ukauthority [106] #ukgovtech,community [106] community,news [97] #civictech,#govtech [92] #govtech,diginomica Top Word Pairs in Tweet in G1:
[28] government,technology [23] top,20 [23] predictions,2020 [20] 20,security [20] security,predictions [20] govtechのグラファーが神戸オフィスを新設,総額約4 [19] 総額約4,5億円の資金調達も [18] technology,game [18] game,changer [15] blockchain,technology Top Word Pairs in Tweet in G2:
[183] #govtech,#stateandlocal [33] #security,#govtech [31] learn,more [27] meet,#govtech100 [18] #publicsafety,#govtech [16] one,those [16] those,votes [14] alpha,team [13] beyond,beltway [13] 2020,#govtech Top Word Pairs in Tweet in G3:
[84] top,20 [84] predictions,2020 [79] security,predictions [78] 20,security [74] #legaltech,#healthtech [70] #cybersecurity,#fintech [67] #gdpr,#govtech [65] #fintech,#legaltech [63] #healthtech,#bugbounty [44] #govtech,#dataprotection Top Word Pairs in Tweet in G4:
[113] #govtech,ukauthority [106] #ukgovtech,community [106] community,news [92] #govtech,diginomica [51] #civictech,#govtech [50] #govtech,govcomputing [47] #govtech,#security [37] #govtech,#cloud [36] #cloud,diginomica [34] diginomica,diginomica_gov Top Word Pairs in Tweet in G5:
[23] #civictech,#govtech [16] tech,help [16] help,governments [16] governments,fight [16] carlos_santiso,#govtech [15] fight,#corruption [13] difference,between [11] between,#civictech [10] #govtech,against [10] against,#corruption Top Word Pairs in Tweet in G6:
[42] voting,machines [38] assessing,voting [38] machines,senate [38] senate,report [38] report,contains [38] contains,entirely [38] entirely,redacted [38] redacted,section [38] section,russian [38] russian,activity Top Word Pairs in Tweet in G7:
[10] sea,level [10] level,rise [8] atlantic,beach [8] rise,vulnerability [6] flood,prevention [6] prevention,programs [6] programs,fema [6] fema,rarely [6] rarely,focus [6] focus,preventing Top Word Pairs in Tweet in G8:
[28] #coo,#dl [20] #ai,dreams [20] dreams,reality [20] reality,write [20] #dl,#ml [20] #ml,#govtech [20] companies,governments [20] governments,educational [20] educational,institutions [20] institutions,citizens Top Word Pairs in Tweet in G9:
[17] women,govtech [13] special,report [10] included,2019 [10] 55,women [10] women,asia [10] asia,pacific [10] pacific,region [9] govtech,special [9] delighted,included [9] 2019,report Top Word Pairs in Tweet in G10:
[28] #dataviz,#cio [25] #cio,#cto [24] #cto,#gio [23] blog,'#dashboards [23] '#dashboards,#arcgis' [23] #arcgis',showing [23] showing,many [23] many,#opsdashboard [23] #opsdashboard,examples [23] examples,#dataviz Top Replied-To in Entire Graph:
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Top Mentioned in Entire Graph:
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Top Tweeters in Entire Graph:
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