The graph represents a network of 2,518 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, 09 May 2022 at 00:38 UTC.
The requested start date was Monday, 09 May 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, 56-minute period from Monday, 25 April 2022 at 00:16 UTC to Sunday, 08 May 2022 at 03:13 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 : 2518
Unique Edges : 2071
Edges With Duplicates : 8366
Total Edges : 10437
Number of Edge Types : 5
Retweet : 3153
MentionsInRetweet : 4425
Mentions : 1390
Tweet : 1369
Replies to : 100
Self-Loops : 1408
Reciprocated Vertex Pair Ratio : 0.0312999041839668
Reciprocated Edge Ratio : 0.0606999070919789
Connected Components : 571
Single-Vertex Connected Components : 356
Maximum Vertices in a Connected Component : 1355
Maximum Edges in a Connected Component : 8636
Maximum Geodesic Distance (Diameter) : 13
Average Geodesic Distance : 5.162253
Graph Density : 0.000509482303497456
Modularity : 0.301519
NodeXL Version : 1.0.1.449
Data Import : The graph represents a network of 2,518 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, 09 May 2022 at 00:38 UTC.
The requested start date was Monday, 09 May 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, 56-minute period from Monday, 25 April 2022 at 00:16 UTC to Sunday, 08 May 2022 at 03:13 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:
[1488] #fintech,#insurtech [1181] #insurtech,#finserv [983] #finserv,#marketing [577] #marketing,#web3 [512] #web3,#neobanks [425] #neobanks,#payments [272] #payments,#100daysofcode [181] #marketing,#payments [130] #100daysofcode,#modelops [129] siftedeu,#fintech Top Word Pairs in Tweet in G1:
[86] digital,government [82] government,summit [50] learn,more [44] zscaler,excited [44] excited,exhibiting [44] exhibiting,years [44] years,jersey [44] jersey,digital [44] summit,make [44] make,sure Top Word Pairs in Tweet in G2:
[1434] #fintech,#insurtech [1132] #insurtech,#finserv [934] #finserv,#marketing [538] #marketing,#web3 [480] #web3,#neobanks [400] #neobanks,#payments [263] #payments,#100daysofcode [181] #marketing,#payments [129] siftedeu,#fintech [122] #100daysofcode,#modelops Top Word Pairs in Tweet in G3:
[65] govtechnews,#cdwsocial [31] digital,equity [27] #vr,#ar [26] envy,year [26] year,course [26] course,catalog [26] catalog,umich [26] umich,interactive [26] interactive,360 [26] 360,degree Top Word Pairs in Tweet in G4:
[24] #edtech,#govtech [18] #fintech,#insurtech [17] #insurtech,#fintech [17] #fintech,#finsevr [17] #ehealth,#iot [17] #blockchain,#technology [16] #insurtech,#finserv [16] #finserv,#marketing [15] #govtech,#ehealth [15] #iot,#ar Top Word Pairs in Tweet in G5:
[81] ciudades,movilidad [77] movilidad,economía [76] economía,digital [53] lt,encuentro [50] encuentro,internacional [50] internacional,ciudades [47] encuentro,ciudades [42] digital,gt [28] 29,abril [25] primer,encuentro Top Word Pairs in Tweet in G6:
[31] fondo,córdoba [31] córdoba,ciudad [31] ciudad,inteligente [22] bid,lab [21] consejo,consultivo [20] consultivo,fondo [19] tuve,gusto [19] gusto,presidir [19] presidir,primera [19] primera,reunión Top Word Pairs in Tweet in G7:
[28] distributed,digital [24] register,learn [24] learn,approach [24] approach,mfa [24] mfa,eliminates [24] eliminates,one [24] one,time [24] time,codes [24] codes,overcome [24] overcome,loopholes Top Word Pairs in Tweet in G8:
[13] innovación,pública [11] #entérate,#hoy [11] #hoy,estuvimos [11] estuvimos,presentes [11] presentes,#southsummit [11] #southsummit,brasil [11] brasil,contando [11] contando,nuestra [11] nuestra,experiencia [11] experiencia,poner Top Word Pairs in Tweet in G9:
[9] #govtech,startups [7] 19th,2022 [6] digital,transformation [6] hanisha,dewan [5] tage,wollt [5] wollt,teil [5] teil,community [5] community,innovativsten [5] innovativsten,#govtech [5] startups,die Top Replied-To in Entire Graph:
Top Replied-To in G2:
Top Replied-To in G3:
Top Replied-To in G6:
Top Replied-To in G7:
Top Replied-To in G8:
Top Replied-To in G9:
Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
Top Mentioned in G2:
Top Mentioned in G3:
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Top Mentioned in G5:
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Top Mentioned in G7:
Top Mentioned in G8:
Top Mentioned in G9:
Top Mentioned in G10:
Top Tweeters in Entire Graph:
Top Tweeters in G1:
Top Tweeters in G2:
Top Tweeters in G3:
Top Tweeters in G4:
Top Tweeters in G5:
Top Tweeters in G6:
Top Tweeters in G7:
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Top Tweeters in G9:
Top Tweeters in G10: