The graph represents a network of 114 Twitter users whose tweets in the requested range contained "opengov", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Thursday, 17 November 2022 at 15:34 UTC.
The requested start date was Thursday, 17 November 2022 at 01:01 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 11-hour, 59-minute period from Thursday, 03 November 2022 at 08:54 UTC to Thursday, 03 November 2022 at 20:53 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 : 114
Unique Edges : 58
Edges With Duplicates : 180
Total Edges : 238
Number of Edge Types : 5
Retweet : 79
MentionsInRetweet : 85
Tweet : 23
Mentions : 46
Replies to : 5
Self-Loops : 26
Reciprocated Vertex Pair Ratio : 0.045045045045045
Reciprocated Edge Ratio : 0.0862068965517241
Connected Components : 16
Single-Vertex Connected Components : 6
Maximum Vertices in a Connected Component : 80
Maximum Edges in a Connected Component : 191
Maximum Geodesic Distance (Diameter) : 5
Average Geodesic Distance : 2.884556
Graph Density : 0.00900481291724888
Modularity : 0.420905
NodeXL Version : 1.0.1.507
Data Import : The graph represents a network of 114 Twitter users whose tweets in the requested range contained "opengov", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Thursday, 17 November 2022 at 15:34 UTC.
The requested start date was Thursday, 17 November 2022 at 01:01 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 11-hour, 59-minute period from Thursday, 03 November 2022 at 08:54 UTC to Thursday, 03 November 2022 at 20:53 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 : opengov
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:
[27] ø,ù [25] ø,ø [25] ù,ø [20] #opengov,reformers [15] civil,society [14] ù,ù [14] opengovpart,#opengov [13] africa,middle [12] middle,east [10] east,regional Top Word Pairs in Tweet in G1:
[27] ø,ù [25] ø,ø [25] ù,ø [14] #opengov,reformers [14] ù,ù [9] civil,society [9] opengovpart,#opengov [7] reformers,continuously [7] define,processes [7] tools,help Top Word Pairs in Tweet in G2:
[7] cfo,council [5] foia,officers [4] council,meeting [4] chief,foia [3] livestreaming,watch [3] council,co [3] officers,cfo [3] watch,chief [3] chaired,directors [3] meeting,cfo Top Word Pairs in Tweet in G3:
[8] undermines,womenâ [8] #opengov,solutions [8] gender,based [8] based,violence [8] leaders,ndi [8] violence,undermines [8] full,participation [8] discuss,#opengov [8] ogp,discuss [8] public,leaders Top Word Pairs in Tweet in G4:
[9] year's,africa [9] east,regional [9] taking,part [9] regional,convention [9] middle,east [9] part,year's [9] convention,open [9] africa,middle [9] counties,taking [9] kenyan,counties Top Word Pairs in Tweet in G6:
[6] happening,plenary [6] processes,impact [6] civil,society [6] chair,civil [6] showcasing,tools [6] tools,processes [6] co,chair [6] opengov,innovation [6] innovation,showcasing [6] plenary,opengov Top Word Pairs in Tweet in G7:
[6] need,more [5] research,more [5] art,need [5] more,research [5] more,evidence [5] œ#opengov,more [5] evidence,methodologies [5] more,science [5] need,open [5] science,art Top Word Pairs in Tweet in G8:
[2] #unstoppabledomains,forsale [2] wallet,dao [2] dao,nft [2] zil,#crypto [2] preservica,crypto [2] #crypto,#identity [2] blockchain,wallet [2] forsale,preservica [2] nft,zil [2] crypto,blockchain Top Word Pairs in Tweet in G9:
[7] #opengov,reforms [7] ambitious,#opengov [5] advance,ambitious [4] years,reformers [4] africa,middle [4] reformers,africa [4] many,years [4] #ogpmorocco2022,first [4] first,time [4] time,many Top Word Pairs in Tweet in G10:
[4] #wpgpoli,#opengov [4] #mbpoli,#wpgpoli [4] µon,prairiedevcon [4] giving,monday [4] monday,winnipeg [4] winnipeg,#mbpoli [4] #opengov,#opendata [4] prairiedevcon,talk [4] short,µon [4] talk,giving Top Replied-To in Entire Graph:
Top Replied-To in G2:
Top Replied-To in G5:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
Top Mentioned in G2:
Top Mentioned in G3:
Top Mentioned in G4:
Top Mentioned in G5:
Top Mentioned in G6:
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:
Top Tweeters in G8:
Top Tweeters in G9:
Top Tweeters in G10: