The graph represents a network of 485 Twitter users whose recent tweets contained "BrookingsMetro", 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 Thursday, 22 July 2021 at 16:53 UTC.
The tweets in the network were tweeted over the 8-day, 3-hour, 13-minute period from Wednesday, 14 July 2021 at 12:39 UTC to Thursday, 22 July 2021 at 15:52 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 : 485
Unique Edges : 1176
Edges With Duplicates : 347
Total Edges : 1523
Number of Edge Types : 5
Mentions : 397
MentionsInRetweet : 688
Retweet : 327
Tweet : 65
Replies to : 46
Self-Loops : 69
Reciprocated Vertex Pair Ratio : 0.0272727272727273
Reciprocated Edge Ratio : 0.0530973451327434
Connected Components : 38
Single-Vertex Connected Components : 28
Maximum Vertices in a Connected Component : 414
Maximum Edges in a Connected Component : 1453
Maximum Geodesic Distance (Diameter) : 7
Average Geodesic Distance : 3.258161
Graph Density : 0.00529522024367385
Modularity : 0.501049
NodeXL Version : 1.0.1.445
Data Import : The graph represents a network of 485 Twitter users whose recent tweets contained "BrookingsMetro", 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 Thursday, 22 July 2021 at 16:53 UTC.
The tweets in the network were tweeted over the 8-day, 3-hour, 13-minute period from Wednesday, 14 July 2021 at 12:39 UTC to Thursday, 22 July 2021 at 15:52 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 : BrookingsMetro
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:
[126] adietomer,jwkane1 [121] jwkane1,jenny_schuetz [121] jenny_schuetz,carolinergeorge [96] advanced,modeling [95] compared,older [95] older,urban [95] urban,cores [94] modeling,consistently [94] consistently,finds [94] finds,higher Top Word Pairs in Tweet in G1:
[121] adietomer,jwkane1 [119] jwkane1,jenny_schuetz [119] jenny_schuetz,carolinergeorge [94] advanced,modeling [92] modeling,consistently [92] consistently,finds [92] finds,higher [92] higher,ghg [92] ghg,pollutant [92] pollutant,intensity Top Word Pairs in Tweet in G2:
[84] building,more [84] more,housing [84] housing,transit [84] transit,rich [84] rich,urban [84] urban,areas [84] areas,suburban [84] suburban,sprawl [84] sprawl,one [84] one,simple Top Word Pairs in Tweet in G3:
[28] small,business [22] small,businesses [16] racial,equity [14] partnership,#sustainablecommunities [13] covid,19 [13] business,owners [12] joeparilla,sifan_liu [12] local,leaders [9] black,workers [9] economic,growth Top Word Pairs in Tweet in G4:
[2] summer,people [2] lower,carbon [2] carbon,footprint [2] urban,areas [2] climate,change [2] suburbs,bad [2] bad,climate [2] climate,demolish [2] demolish,suburbs Top Word Pairs in Tweet in G5:
[5] good,news [5] news,rural [5] rural,america [5] america,varuralcenter [5] varuralcenter,virginiaeda [5] virginiaeda,agforestryva [5] agforestryva,brookingsmetro [5] brookingsmetro,amy_liuw [5] amy_liuw,markmuro1 [5] markmuro1,n_arnosti Top Word Pairs in Tweet in G6:
[2] building,solar [2] solar,farms [2] farms,build [2] build,middle [2] middle,class [2] class,sunrisemvmt [2] sunrisemvmt,varshprakash [2] varshprakash,leahstokes [2] leahstokes,khayhoe [2] khayhoe,doctorvive Top Word Pairs in Tweet in G7:
[3] definitely,nashville [3] nashville,specific [3] specific,brookingsmetro [3] brookingsmetro,yarbro [3] yarbro,wilderjace [3] wilderjace,mcminndems [3] mcminndems,changetn_ [3] changetn_,bradbatt [3] bradbatt,tndistrict1 [3] tndistrict1,amcotn Top Word Pairs in Tweet in G8:
[5] great,brookingsmetro [5] brookingsmetro,primer [5] primer,community [5] community,ownership [5] ownership,land [5] land,lohplaces [5] lohplaces,hannamlove [5] hannamlove,case [5] case,study [5] study,dtcrenshaw Top Word Pairs in Tweet in G9:
[10] making,easier [10] easier,more [10] more,people [10] people,live [10] live,cities [10] cities,hugely [10] hugely,positive [10] positive,climate [10] climate,effects Top Word Pairs in Tweet in G10:
[6] large,#placemaking [6] #placemaking,project [6] project,equity [6] equity,central [6] central,focus [6] focus,brookingsmetro [6] brookingsmetro,jvey1 [6] jvey1,project [6] project,megwalker6 [6] megwalker6,fred_kent Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G3:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
Top Mentioned in G3:
Top Mentioned in G5:
Top Mentioned in G6:
Top Mentioned in G7:
Top Mentioned in G8:
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: