The graph represents a network of 2,875 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, 04 July 2022 at 00:38 UTC.
The requested start date was Monday, 04 July 2022 at 00:01 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, 2-hour, 53-minute period from Monday, 20 June 2022 at 00:01 UTC to Sunday, 03 July 2022 at 02:54 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 : 2875
Unique Edges : 2796
Edges With Duplicates : 7670
Total Edges : 10466
Number of Edge Types : 5
Retweet : 2645
MentionsInRetweet : 4501
Tweet : 1417
Mentions : 1825
Replies to : 78
Self-Loops : 1467
Reciprocated Vertex Pair Ratio : 0.0385939036381514
Reciprocated Edge Ratio : 0.0743195266272189
Connected Components : 626
Single-Vertex Connected Components : 410
Maximum Vertices in a Connected Component : 1501
Maximum Edges in a Connected Component : 8263
Maximum Geodesic Distance (Diameter) : 17
Average Geodesic Distance : 5.37595
Graph Density : 0.000511330973344226
Modularity : 0.383549
NodeXL Version : 1.0.1.449
Data Import : The graph represents a network of 2,875 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, 04 July 2022 at 00:38 UTC.
The requested start date was Monday, 04 July 2022 at 00:01 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, 2-hour, 53-minute period from Monday, 20 June 2022 at 00:01 UTC to Sunday, 03 July 2022 at 02:54 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:
[794] #metaverse,#nft [670] #nft,#payments [623] #digital,#python [592] #data,#analytics [551] #python,#flutter [509] #payments,#data [397] #flutter,#marketing [386] #analytics,#ai [332] #ai,#digital [318] #analytics,#digital Top Word Pairs in Tweet in G1:
[60] government,technology [40] smart,cities [39] legacy,systems [38] bridging,#digitaldivide [38] #digitaldivide,migrating [38] migrating,legacy [38] systems,cloud [38] cloud,shift [38] shift,smart [38] cities,starts Top Word Pairs in Tweet in G2:
[659] #metaverse,#nft [570] #nft,#payments [544] #digital,#python [510] #data,#analytics [490] #python,#flutter [438] #payments,#data [369] #flutter,#marketing [336] #analytics,#ai [296] #ai,#digital [271] #tech,trends Top Word Pairs in Tweet in G3:
[126] #metaverse,#nft [94] #nft,#payments [81] #fintech,#finsevr [77] #insurtech,#fintech [76] #data,#analytics [76] #digital,#python [73] #blockchain,#technology [67] stratorob,#blockchain [67] #ai,#edtech [67] #payments,#data Top Word Pairs in Tweet in G4:
[18] govtechnews,#cdwsocial [16] task,forces [15] #stategov,prepare [15] prepare,cities [15] cities,#climatechange [15] #climatechange,starting [15] starting,point [15] point,utilize [15] utilize,tech [15] tech,#publicworks Top Word Pairs in Tweet in G5:
[12] sector,público [12] bootcamp,#govtech [11] cien,mejores [11] mejores,ideas [11] ideas,innovar [11] biggest,#tech [11] #tech,trends [11] trends,transforming [11] transforming,governments [11] governments,2022 Top Word Pairs in Tweet in G6:
[12] start,ups [12] govtech,gipfel [12] bericht,public_germany [12] public_germany,soprasteria [10] govtech,campus [10] heute,launcht [10] launcht,gemeinsamer [10] gemeinsamer,bericht [10] soprasteria,thema [10] thema,öffentliche Top Word Pairs in Tweet in G7:
[84] #whereeverythingconnects,#govtech [67] public,sector [47] learn,more [46] more,#whereeverythingconnects [39] white,paper [35] digital,workplace [30] solutions,bring [30] sd,wan [30] versa,networks [29] aluenterprise,sd Top Word Pairs in Tweet in G8:
[2] ajohnso50141696,calliem19373157 [2] fueldog3,spacesvector [2] btchnmarilyn,originalgoalie [2] originalgoalie,realvioletbloom [2] realvioletbloom,mirandaisrisen [2] jackjackedme,ssherow [2] ssherow,dynamex [2] dynamex,russettrichard [2] russettrichard,jamess33677101 [2] jamess33677101,charles900811 Top Word Pairs in Tweet in G9:
[3] ky,reached [3] reached,find [3] find,part [3] part,program [2] gibsonmainframe,ky [2] yokalli2,lifelessai [2] lifelessai,b3n_5mash [2] b3n_5mash,blackhatnanny [2] blackhatnanny,mysocalledninja [2] mysocalledninja,pacificdisinfo 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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Top Tweeters in G10: