The graph represents a network of 3,264 Twitter users whose tweets in the requested range contained "#CRE", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Thursday, 17 September 2020 at 17:25 UTC.
The requested start date was Thursday, 17 September 2020 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 9-day, 9-hour, 30-minute period from Monday, 07 September 2020 at 14:29 UTC to Thursday, 17 September 2020 at 00:00 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 : 3264
Unique Edges : 2626
Edges With Duplicates : 8101
Total Edges : 10727
Number of Edge Types : 5
Retweet : 1631
MentionsInRetweet : 2220
Tweet : 4421
Mentions : 2267
Replies to : 188
Self-Loops : 4464
Reciprocated Vertex Pair Ratio : 0.059304084720121
Reciprocated Edge Ratio : 0.111968009140246
Connected Components : 915
Single-Vertex Connected Components : 618
Maximum Vertices in a Connected Component : 1645
Maximum Edges in a Connected Component : 6910
Maximum Geodesic Distance (Diameter) : 14
Average Geodesic Distance : 5.069297
Graph Density : 0.000328719060409944
Modularity : 0.329577
NodeXL Version : 1.0.1.440
Data Import : The graph represents a network of 3,264 Twitter users whose tweets in the requested range contained "#CRE", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Thursday, 17 September 2020 at 17:25 UTC.
The requested start date was Thursday, 17 September 2020 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 9-day, 9-hour, 30-minute period from Monday, 07 September 2020 at 14:29 UTC to Thursday, 17 September 2020 at 00:00 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 : #CRE
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:
[489] commercial,estate [355] #cre,#realestate [281] #cre,#commercialrealestate [183] covid,19 [180] #cre,#office [161] #covid,19 [154] office,space [149] gt,gt [143] #cre,#tenanttips [117] know,#cre Top Word Pairs in Tweet in G1:
[118] gt,gt [71] commercial,estate [57] #cre,#commercialrealestate [52] #roc,#cre [47] national,#cre [45] #commercialrealestate,#cre [38] rick,altier [37] #cre,#realestate [30] info,#cre [29] more,information Top Word Pairs in Tweet in G2:
[37] #retail,#cre [33] commercial,estate [33] #cre,#commercialrealestate [21] #cre,#realestate [19] commercial,investment [17] wsj,#cre [14] #cre,#retail [13] #cre,#office [13] asset,class [12] #industrial,market Top Word Pairs in Tweet in G3:
[79] 2020,next [79] next,generation [79] generation,honoree [19] #cre,#commercialrealestate [13] ma,#cre [10] ebiconsulting,appoints [10] appoints,nolan [10] nolan,jeffrey [10] jeffrey,previte [10] previte,co Top Word Pairs in Tweet in G4:
[55] #office,#multitenantoffice [44] #florida,#cre [31] #retail,#streetretail [29] #illinois,#cre [21] #chicago,#illinois [20] #ohio,#cre [19] welcome,tbl [19] tbl,#cre [19] #cre,member [18] #land,#otherland Top Word Pairs in Tweet in G5:
[205] commercial,estate [154] #covid,19 [144] #cre,#office [140] #cre,#tenanttips [110] know,#cre [89] space,#cre [83] #office,#warehouse [83] office,space [78] #cre,#leasing [76] covid,19 Top Word Pairs in Tweet in G6:
[44] #cre,#commercialrealestate [40] commercial,estate [40] #cre,#highdesert [38] #highdesert,#inlandempire [34] #cre,#realestate [33] #inlandempire,#realestate [32] #realestate,#land [32] #land,#investments [30] #investments,#development [30] #development,#industrial Top Word Pairs in Tweet in G7:
[55] #cre,#commercialrealestate [26] covid,19 [17] today,reads [14] reads,#cre [14] #cre,#mustreads [13] commercial,estate [10] during,covid [9] york,times [9] bankruptcy,reports [9] q2,2020 Top Word Pairs in Tweet in G8:
[139] #cre,#realestate [16] countdown,#tonaiop [16] #tonaiop,#rex2020 [13] commercial,estate [13] covid,19 [13] q2,2020 [13] #rex2020,congratulations [13] congratulations,team [9] 2020,according [9] statistics,canada Top Word Pairs in Tweet in G9:
[35] #arizona,#cre [21] #cre,#retail [19] space,available [11] #phoenix,#arizona [10] plus,more [9] retail,space [7] managing,director [7] #retail,#neighborhoodcenter [7] shop,space [7] psbj,#cre Top Word Pairs in Tweet in G10:
[11] latest,estate [11] estate,news [11] news,canada [11] canada,#stalbert [11] #stalbert,#stalbertre [11] #stalbertre,#yegre [11] #yegre,#yvrre [11] #yvrre,#yeg [10] #yeg,#yyz [10] mario,toneguzzi Top Replied-To in Entire Graph:
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Top Replied-To in G5:
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Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Tweeters in Entire Graph:
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Top Tweeters in G10: