The graph represents a network of 4,102 Twitter users whose tweets in the requested range contained "Worldbank (environment OR climate OR warming OR ecological OR planet OR global)", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Tuesday, 12 November 2019 at 14:44 UTC.
The requested start date was Monday, 11 November 2019 at 01:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 13-day, 23-hour, 50-minute period from Monday, 28 October 2019 at 01:02 UTC to Monday, 11 November 2019 at 00:53 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 : 4102
Unique Edges : 6422
Edges With Duplicates : 5883
Total Edges : 12305
Number of Edge Types : 3
Mentions : 11592
Tweet : 449
Replies to : 264
Self-Loops : 449
Reciprocated Vertex Pair Ratio : 0.0162941600576784
Reciprocated Edge Ratio : 0.0320658342792281
Connected Components : 175
Single-Vertex Connected Components : 99
Maximum Vertices in a Connected Component : 3720
Maximum Edges in a Connected Component : 11936
Maximum Geodesic Distance (Diameter) : 12
Average Geodesic Distance : 3.670548
Graph Density : 0.000418967629994991
Modularity : 0.459307
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 4,102 Twitter users whose tweets in the requested range contained "Worldbank (environment OR climate OR warming OR ecological OR planet OR global)", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Tuesday, 12 November 2019 at 14:44 UTC.
The requested start date was Monday, 11 November 2019 at 01:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 13-day, 23-hour, 50-minute period from Monday, 28 October 2019 at 01:02 UTC to Monday, 11 November 2019 at 00:53 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 : Worldbank (environment OR climate OR warming OR ecological OR planet OR global)
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 : Followers
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[252] ø,ø [205] ø,ù [172] ðÿ,ðÿ [170] climate,change [169] world,bank [165] ù,ø [157] top,10 [150] business,climate [142] davidmalpasswbg,president [141] president,worldbank Top Word Pairs in Tweet in G1:
[79] business,climate [79] commodity,markets [79] markets,outlook [67] worldbank,commodity [64] worldbank,worldbank [58] doing,business [56] global,value [51] improve,business [50] value,chains [40] global,trade Top Word Pairs in Tweet in G2:
[57] income,countries [48] low,income [48] countries,livelihoods [48] livelihoods,depend [48] depend,#naturalcapital [48] #naturalcapital,governments [48] governments,lose [48] 12,billion [48] billion,potential [47] lose,7â Top Word Pairs in Tweet in G3:
[52] joelosteen,psraymccauley [52] psraymccauley,joshuamccauley [52] joshuamccauley,celliersj1 [52] celliersj1,firstrand [52] firstrand,standardbankza [52] standardbankza,mesirowfin [52] mesirowfin,blackrock [52] blackrock,ellevest [52] ellevest,lisastone [52] lisastone,salliekrawcheck Top Word Pairs in Tweet in G4:
[141] davidmalpasswbg,president [135] president,worldbank [133] assurance,davidmalpasswbg [133] worldbank,6b [133] 6b,lending [133] lending,india [133] india,appreciating [133] appreciating,vision [132] omkar_raii,assurance [127] vision,hon Top Word Pairs in Tweet in G5:
[86] ðÿ,ðÿ [70] global,price [70] price,gender [70] gender,inequality [70] inequality,link [70] link,gt [70] gt,gt [70] gt,worldbank [70] worldbank,antgrasso [70] antgrasso,#womenintech Top Word Pairs in Tweet in G6:
[26] #africaspulse,report [17] new,#africaspulse [16] find,out [15] climate,change [14] four,ten [14] over,416 [14] 416,million [14] lived,below [14] below,1 [14] 1,90 Top Word Pairs in Tweet in G7:
[30] alston_unsr,sfparr [30] sfparr,thenewschool [30] thenewschool,sfu [30] sfu,worldbank [29] worldbank,unicef [29] unicef,harvardchansph [29] harvardchansph,fudanuniversity [29] fudanuniversity,kadijaferryman [27] kadijaferryman,datasociety [24] global,action Top Word Pairs in Tweet in G8:
[178] ø,ø [149] ø,ù [122] ù,ø [81] ù,ù [35] global,financial [26] bank,regulation [24] business,climate [22] ùšø,ø [20] ù,ùš [19] development,report Top Word Pairs in Tweet in G9:
[26] president,davidmalpasswbgâ [22] world,bank [15] worldbank,join [15] join,tuesday [15] tuesday,november [15] november,5 [15] 5,3 [15] 3,pm [15] pm,edt [15] edt,discussion Top Word Pairs in Tweet in G10:
[27] world,bank [8] global,financial [6] climate,change [6] doing,business [6] development,report [5] bank,report [5] 5,ways [5] ways,reduce [5] reduce,drivers [5] drivers,#climatechange Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
Top Replied-To in G3:
Top Replied-To in G4:
Top Replied-To in G5:
Top Replied-To in G6:
Top Replied-To in G7:
Top Replied-To in G9:
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: