The graph represents a network of 5,679 Twitter users whose tweets in the requested range contained "worldbank", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Thursday, 08 September 2022 at 12:26 UTC.
The requested start date was Thursday, 08 September 2022 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 2-day, 12-hour, 12-minute period from Monday, 05 September 2022 at 11:39 UTC to Wednesday, 07 September 2022 at 23:51 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 : 5679
Unique Edges : 7665
Edges With Duplicates : 19027
Total Edges : 26692
Number of Edge Types : 5
Retweet : 6335
MentionsInRetweet : 12694
Mentions : 6696
Tweet : 360
Replies to : 607
Self-Loops : 403
Reciprocated Vertex Pair Ratio : 0.00525783619817998
Reciprocated Edge Ratio : 0.0104606718970026
Connected Components : 226
Single-Vertex Connected Components : 84
Maximum Vertices in a Connected Component : 5070
Maximum Edges in a Connected Component : 25941
Maximum Geodesic Distance (Diameter) : 9
Average Geodesic Distance : 3.323506
Graph Density : 0.000462485116464191
Modularity : 0.400594
NodeXL Version : 1.0.1.504
Data Import : The graph represents a network of 5,679 Twitter users whose tweets in the requested range contained "worldbank", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Thursday, 08 September 2022 at 12:26 UTC.
The requested start date was Thursday, 08 September 2022 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 2-day, 12-hour, 12-minute period from Monday, 05 September 2022 at 11:39 UTC to Wednesday, 07 September 2022 at 23:51 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
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:
[1375] tigrayan,people [1373] people,defenseless [1373] defenseless,abiyahmedali [1373] abiyahmedali,govt [1373] govt,conspiring [1373] amharas,forces [1287] conspiring,govt [1287] govt,amharas [772] #s3199,#hr6600 [772] #hr6600,members Top Word Pairs in Tweet in G1:
[152] food,price [152] price,inflation [87] inflation,remains [87] worldbank,group [85] update,food [79] covid,19 [72] low,income [70] #foodsecurity,update [70] 92,low [69] remains,challenge Top Word Pairs in Tweet in G2:
[1334] tigrayan,people [1333] people,defenseless [1333] defenseless,abiyahmedali [1333] abiyahmedali,govt [1333] govt,conspiring [1333] amharas,forces [1249] conspiring,govt [1249] govt,amharas [497] humanitarian,assistance [496] millions,#tigray Top Word Pairs in Tweet in G3:
[152] tigray's,children [152] children,vaccinated [152] vaccinated,before [152] before,war [152] war,over [152] over,90 [152] 90,such [152] such,criminal [152] criminal,waste [152] waste,young Top Word Pairs in Tweet in G4:
[608] #s3199,#hr6600 [608] #hr6600,members [608] members,congress [608] congress,press [608] press,potus [608] designate,tps [605] addition,supporting [605] supporting,#s3199 [605] potus,designate [605] tps,#ethiopia Top Word Pairs in Tweet in G5:
[232] #savioroftheworld,nostradamus [232] nostradamus,france [232] france,prediction [232] prediction,ocean [232] ocean,three [232] three,sides [232] sides,great [232] great,saint [232] saint,born [219] jyotijy66529274,#savioroftheworld Top Word Pairs in Tweet in G6:
[36] pmoindia,rbi [35] finminindia,nsitharaman [34] narendramodi,pmoindia [34] rbi,finminindia [34] icj_asia,abpnews [24] abpnews,mumbaimirror [24] mumbaimirror,httweets [22] sunnyfernandes,narendramodi [18] nsitharaman,#boycottunitybanksfb [18] #boycottunitybanksfb,#pmcbankcrisis Top Word Pairs in Tweet in G7:
[68] imfnews,worldbank [60] worldbank,worldbanksasia [55] worldbanksasia,stop [53] poverty,inequality [41] attention,imfnews [39] inequality,time [39] time,unconditional [37] fueling,poverty [36] sri,lanka [33] stop,fueling Top Word Pairs in Tweet in G8:
[9] ukinsierraleone,usembfreetown [8] euinsierraleone,ukinsierraleone [8] usembfreetown,undpsierraleone [7] undpsierraleone,unsierraleone [7] unsierraleone,ecowas_cedeao [7] ecowas_cedeao,_africanunion [7] _africanunion,worldbank [7] worldbank,imfafrica [6] peoplespowerin1,euinsierraleone [6] imfafrica,presidentbio Top Word Pairs in Tweet in G9:
[12] world,bank [4] bank,group [3] 31,billion [2] pastor,emmanuel [2] emmanuel,gbaruko [2] climate,change [2] south,asia [2] #imf,#worldbank [2] climate,finance [2] finance,31 Top Word Pairs in Tweet in G10:
[12] países,latinoamericanos [11] lectura,recomendada [11] recomendada,gt [11] gt,profundizar [11] profundizar,acuerdos [11] acuerdos,comerciales [11] comerciales,existentes [11] existentes,países [11] latinoamericanos,podría [11] podría,aumentar Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Replied-To in G6:
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Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Mentioned in G7:
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Top Mentioned in G10:
Top Tweeters in Entire Graph:
Top Tweeters in G1:
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Top Tweeters in G5:
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Top Tweeters in G10: