The graph represents a network of 1,470 Twitter users whose recent tweets contained "#eparticipation OR #localgov", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 18,000 tweets. The network was obtained from Twitter on Tuesday, 02 August 2022 at 18:10 UTC.
The tweets in the network were tweeted over the 10-day, 2-hour, 46-minute period from Saturday, 23 July 2022 at 14:45 UTC to Tuesday, 02 August 2022 at 17:31 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 : 1470
Unique Edges : 2228
Edges With Duplicates : 1793
Total Edges : 4021
Number of Edge Types : 5
MentionsInRetweet : 977
Mentions : 1314
Retweet : 748
Tweet : 933
Replies to : 49
Self-Loops : 938
Reciprocated Vertex Pair Ratio : 0.0370531822144725
Reciprocated Edge Ratio : 0.07145859604876
Connected Components : 189
Single-Vertex Connected Components : 73
Maximum Vertices in a Connected Component : 750
Maximum Edges in a Connected Component : 2229
Maximum Geodesic Distance (Diameter) : 14
Average Geodesic Distance : 6.198816
Graph Density : 0.00110167960989706
Modularity : 0.569536
NodeXL Version : 1.0.1.449
Data Import : The graph represents a network of 1,470 Twitter users whose recent tweets contained "#eparticipation OR #localgov", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 18,000 tweets. The network was obtained from Twitter on Tuesday, 02 August 2022 at 18:10 UTC.
The tweets in the network were tweeted over the 10-day, 2-hour, 46-minute period from Saturday, 23 July 2022 at 14:45 UTC to Tuesday, 02 August 2022 at 17:31 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 : TwitterSearch
Graph Term : #eparticipation OR #localgov
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 Color : In-Degree
Vertex Radius : In-Degree
Vertex Alpha : In-Degree
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[441] #localgov,#govjobs [441] #govjobs,#govhr [435] apply,#localgov [84] local,government [83] #ukhousing,#localgov [66] county,council [58] #localgov,#localgovjobs [56] council,#localgov [44] part,time [43] #mdbiz,#smallbusiness Top Word Pairs in Tweet in G1:
[17] help,#localgov [16] social,care [15] martin,routledge [15] routledge,socfuture [15] socfuture,people [15] people,#localgov [15] #localgov,support [15] support,providers [15] providers,#conservativeleadership [15] #conservativeleadership,candidates Top Word Pairs in Tweet in G2:
[83] #ukhousing,#localgov [23] cipfa,cihhousing [18] cihhousing,lganews [15] scotgov,welshgovernment [13] #localgov,cipfa [10] awics,offers [10] luhc,scotgov [10] cosla,sfha_hq [9] housingombuds,severe [9] severe,maladministration Top Word Pairs in Tweet in G3:
[11] #localgov,insight [11] insight,working [11] working,programming [11] programming,content [11] content,emerging [11] emerging,topics [11] topics,practitioners [11] practitioners,like [11] like,covered [11] covered,workshops Top Word Pairs in Tweet in G4:
[10] #ldreporter,#ldr [10] #ldr,#bbc [10] #bbc,#localgov [8] agenda,#ldreporter [8] light,rail [7] shaznawaz1,nicoladay78 [7] cambspboroca,nikjohnsonca [6] significant,judgement [6] judgement,#grenfell [6] #grenfell,case Top Word Pairs in Tweet in G5:
[9] #localgov,#councils [6] local,government [6] ca,county [6] county,news [6] #cacounties,#cagov [6] #cagov,#localgov [6] #localgov,#countygov [6] #countygov,#california [6] #california,#caeconomy [6] #caeconomy,#catransportation Top Word Pairs in Tweet in G6:
[43] #mdbiz,#smallbusiness [36] #maryland,#oceancity [36] #econdev,#wkdev [35] #mdpolitics,#mdbiz [34] #smallbusiness,#arpa [34] #arpa,#econdev [31] #oceancity,#mdpolitics [23] #mdcounties,#localgov [21] #localgov,#mdcounties [15] #wkdev,#mdcounties Top Word Pairs in Tweet in G7:
[17] apply,#platformawards [17] european,#localgov [17] #localgov,cooperation [17] cooperation,partnership [17] partnership,project [17] project,apply [14] uclg,world [11] july,apply [11] time,check [11] check,info Top Word Pairs in Tweet in G8:
[18] #cdnmuni,#localgov [11] public,lecture [11] megan,lohmann [11] lohmann,maya [11] maya,chorobik [11] chorobik,bc_cea [11] 27,noon [11] noon,pt [9] municipal,world [9] local,government Top Word Pairs in Tweet in G9:
[15] county,council [11] city,council [10] digital,services [9] #mentalhealth,support [8] norwich,city [7] essex,county [7] #recruiting,interested [7] interested,working [7] working,website [7] website,information Top Word Pairs in Tweet in G10:
[7] delighted,share [7] share,news [7] news,#salford [7] #salford,youth [7] youth,zone [7] zone,scheme [7] scheme,partnership [7] partnership,hideout_yz [7] hideout_yz,big [7] big,expansion Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G3:
Top Replied-To in G4:
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:
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: