The graph represents a network of 8,162 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, 17 December 2020 at 13:37 UTC.
The requested start date was Thursday, 17 December 2020 at 01:01 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 3-day, 9-hour, 17-minute period from Sunday, 13 December 2020 at 15:40 UTC to Thursday, 17 December 2020 at 00:58 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 : 8162
Unique Edges : 10714
Edges With Duplicates : 18109
Total Edges : 28823
Number of Edge Types : 5
Tweet : 766
MentionsInRetweet : 10267
Retweet : 4437
Mentions : 11803
Replies to : 1550
Self-Loops : 835
Reciprocated Vertex Pair Ratio : 0.0163185776045789
Reciprocated Edge Ratio : 0.0321131148523156
Connected Components : 412
Single-Vertex Connected Components : 212
Maximum Vertices in a Connected Component : 7127
Maximum Edges in a Connected Component : 27393
Maximum Geodesic Distance (Diameter) : 10
Average Geodesic Distance : 3.429
Graph Density : 0.000250577682819847
Modularity : 0.458583
NodeXL Version : 1.0.1.441
Data Import : The graph represents a network of 8,162 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, 17 December 2020 at 13:37 UTC.
The requested start date was Thursday, 17 December 2020 at 01:01 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 3-day, 9-hour, 17-minute period from Sunday, 13 December 2020 at 15:40 UTC to Thursday, 17 December 2020 at 00:58 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:
[413] world,bank [396] covid,19 [273] dato,nivel [273] nivel,mundial [273] mundial,mayor [273] mayor,desindustrialización [273] desindustrialización,periodo [273] periodo,2015 [273] 2015,2019 [273] 2019,argentina Top Word Pairs in Tweet in G1:
[123] mobilepunch,worldbank [100] need,loan [99] saharareporters,worldbank [96] worldbank,worldbankafrica [95] hello,worldbank [90] worldbank,name [89] nigerian,need [87] glad,borrow [86] loan,glad [83] billion,loan Top Word Pairs in Tweet in G2:
[129] middle,class [120] finminindia,nsitharaman [117] rbi,finminindia [115] pmoindia,rbi [112] narendramodi,pmoindia [110] nsitharaman,fayedsouza [110] icj_asia,abpnews [109] abpnews,mumbaimirror [99] sunnyfernandes,narendramodi [76] rbi,dasshaktikanta Top Word Pairs in Tweet in G3:
[25] informal,sector [21] pattyhajdu,kamalkheralib [16] covid,19 [16] informal,workers [16] ap,dw [16] wef,worldbank [15] climate,research [15] dw,bbc [14] learn,more [13] jobs,urban Top Word Pairs in Tweet in G4:
[82] sudanese,people [81] good,news [80] news,sudanese [80] people,sudanpmhamdok [80] sudanpmhamdok,urgent [80] urgent,begin [80] begin,arrears [80] arrears,clearance [80] clearance,unlock [79] davidmalpasswbg,good Top Word Pairs in Tweet in G5:
[273] dato,nivel [273] nivel,mundial [273] mundial,mayor [273] mayor,desindustrialización [273] desindustrialización,periodo [273] periodo,2015 [273] 2015,2019 [273] 2019,argentina [273] argentina,fuente [272] riellodecba,dato Top Word Pairs in Tweet in G6:
[215] existe,pandemia [215] pandemia,américa [215] américa,latina [215] latina,caribe [215] caribe,violencia [215] violencia,género [215] género,covid [215] covid,19 [215] 19,dejado [215] dejado,millones Top Word Pairs in Tweet in G7:
[22] vision,#futureoflearning [20] emphasizes,five [20] #education,system [19] #futureoflearning,emphasizes [19] five,pillars [19] pillars,basic [19] basic,#education [19] system,enable [19] enable,learning [17] wbg_education,vision Top Word Pairs in Tweet in G8:
[38] world,bank [23] learn,more [13] covid,19 [5] #economy,growth [4] #worldbank,#india [4] nigeria,money [4] bank,approves [4] व,त [4] #externaldebt,learn [4] modeled,ilo Top Word Pairs in Tweet in G9:
[43] moglsd_ug,partnership [43] partnership,worldbank [40] don,miss [39] worldbank,organised [34] organised,webinar [33] economic,empowerment [29] #empowerugwomen,don [29] miss,moglsd_ug [26] moglsd_ug,worldbank [26] webinar,status Top Word Pairs in Tweet in G10:
[37] imfnews,worldbank [31] worldbank,imfnews [23] international,lending [23] lending,agencies [23] agencies,looking [23] looking,give [23] give,money [23] money,please [23] please,demand [23] demand,nigeria Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Replied-To in G7:
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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:
Top Tweeters in G1:
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Top Tweeters in G10: