The graph represents a network of 3,812 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, 02 December 2019 at 07:08 UTC.
The requested start date was Monday, 02 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 11-day, 21-hour, 17-minute period from Tuesday, 19 November 2019 at 16:19 UTC to Sunday, 01 December 2019 at 13:36 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 : 3812
Unique Edges : 4650
Edges With Duplicates : 3534
Total Edges : 8184
Number of Edge Types : 3
Mentions : 6817
Replies to : 100
Tweet : 1267
Self-Loops : 1267
Reciprocated Vertex Pair Ratio : 0.0395846852693056
Reciprocated Edge Ratio : 0.0761548064918851
Connected Components : 590
Single-Vertex Connected Components : 392
Maximum Vertices in a Connected Component : 2595
Maximum Edges in a Connected Component : 6593
Maximum Geodesic Distance (Diameter) : 14
Average Geodesic Distance : 5.226081
Graph Density : 0.000330820128291578
Modularity : 0.558193
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 3,812 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, 02 December 2019 at 07:08 UTC.
The requested start date was Monday, 02 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 11-day, 21-hour, 17-minute period from Tuesday, 19 November 2019 at 16:19 UTC to Sunday, 01 December 2019 at 13:36 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:
[618] voting,machines [541] senate,report [541] report,contains [541] contains,entirely [541] entirely,redacted [541] redacted,section [540] assessing,voting [540] machines,senate [540] section,russian [540] russian,activity Top Word Pairs in Tweet in G1:
[616] voting,machines [540] senate,report [540] report,contains [540] contains,entirely [540] entirely,redacted [540] redacted,section [539] assessing,voting [539] machines,senate [539] section,russian [539] russian,activity Top Word Pairs in Tweet in G2:
[143] #govtech,#stateandlocal [32] login,required [32] required,access [32] register,today [29] access,news [29] news,links [29] links,over [29] over,2400 [27] latest,#technews [26] #security,#govtech Top Word Pairs in Tweet in G3:
[29] government,technology [15] chief,algorithms [15] creates,chief [14] algorithms,officer [14] officer,position [13] york,city [13] city,creates [12] 50,years [12] civic,tech [10] collaboration,key Top Word Pairs in Tweet in G4:
[92] #govtech,ukauthority [61] #govtech,diginomica [28] govtechcloud,#ukgovtech [28] #ukgovtech,community [28] community,news [24] dreamforce,2019 [24] public,sector [23] govtech,france [19] services,publics [19] start,ups Top Word Pairs in Tweet in G5:
[31] aclima,aidtechnology [31] aidtechnology,ambiencedata [31] ambiencedata,amcsgroup1 [31] amcsgroup1,auntbertha [31] auntbertha,autogridsystems [31] autogridsystems,azavea [31] azavea,blackberry [31] blackberry,getblyncsy [20] #analytical,#report [20] dk_analytics,aclima Top Word Pairs in Tweet in G6:
[21] américa,latina [18] gobierno,abierto [17] abierto,innovador [14] #cali,segundo [14] segundo,día [14] día,trabajo [14] trabajo,red [14] red,ocdeenespanol [14] ocdeenespanol,gobierno [14] innovador,américa Top Word Pairs in Tweet in G7:
[102] #govtech,diginomica [79] #ukgovtech,community [79] community,news [61] #govtech,ukauthority [52] #govtech,#security [35] #govtech,govcomputing [35] diginomica,diginomica_gov [34] dreamforce,2019 [33] #govtech,publictech [19] digital,transformation Top Word Pairs in Tweet in G8:
[50] around,world [49] millions,people [49] people,around [49] world,continue [49] continue,suffer [49] suffer,poverty [49] poverty,#data [49] #data,#technology [49] #technology,enable [49] enable,governments Top Word Pairs in Tweet in G9:
[21] #iot,#iiot [19] #iiot,#govtech [12] #govtech,#statelocalit [12] #bigdata,#datascience [11] #cio,#cto [9] #govtech,#smes [9] #smes,#digitaltransformation [9] boozallen,#bigdata [8] time,value [8] #it,#cio Top Word Pairs in Tweet in G10:
[40] #iot,#iiot [27] #aia,#apwa [27] smart,cities [25] #smartcities,#iot [24] #iiot,#govtech [21] congestion,pricing [15] smart,city [14] #govtech,#aia [13] #apwa,#planning [10] #planning,#cto Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Replied-To in G4:
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Top Replied-To in G9:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Mentioned in G10:
Top Tweeters in Entire Graph:
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Top Tweeters in G10: