The graph represents a network of 5,348 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, 13 October 2022 at 12:28 UTC.
The requested start date was Thursday, 13 October 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, 13-hour, 15-minute period from Sunday, 09 October 2022 at 18:48 UTC to Wednesday, 12 October 2022 at 08:04 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 : 5348
Unique Edges : 7746
Edges With Duplicates : 19966
Total Edges : 27712
Number of Edge Types : 5
Retweet : 6088
MentionsInRetweet : 13846
Mentions : 6779
Replies to : 603
Tweet : 396
Self-Loops : 461
Reciprocated Vertex Pair Ratio : 0.00720027962250961
Reciprocated Edge Ratio : 0.0142976124375347
Connected Components : 273
Single-Vertex Connected Components : 127
Maximum Vertices in a Connected Component : 4610
Maximum Edges in a Connected Component : 26664
Maximum Geodesic Distance (Diameter) : 12
Average Geodesic Distance : 3.694482
Graph Density : 0.000503850991035173
Modularity : 0.368483
NodeXL Version : 1.0.1.506
Data Import : The graph represents a network of 5,348 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, 13 October 2022 at 12:28 UTC.
The requested start date was Thursday, 13 October 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, 13-hour, 15-minute period from Sunday, 09 October 2022 at 18:48 UTC to Wednesday, 12 October 2022 at 08:04 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:
[918] #imf,worldbank [903] war,crimes [752] preparing,financially [727] #abiy,#isaias [647] imfnews,worldbank [643] genocide,#tigray [524] continue,bombarded [522] worldbank,antonellabassa3 [520] jorgedajani,wbg_ida [517] antonellabassa3,jorgedajani Top Word Pairs in Tweet in G1:
[162] annual,meetings [159] worldbank,group [102] worldbank,latest [101] imfnews,worldbank [87] latest,worldbank [86] price,inflation [86] food,price [82] countries,highest [82] worldbank,assessment [82] inflation,latest Top Word Pairs in Tweet in G2:
[305] imfnews,worldbank [134] worldbank,imfnews [131] annual,meetings [116] sponsoring,#tigraygenocide [116] #tigraygenocide,#tigrayissuffering [116] funding,sponsoring [116] worldbank,source [116] source,funding [84] #tigrayissuffering,#tigrayunderat [68] fascist,regime Top Word Pairs in Tweet in G3:
[905] #imf,worldbank [891] war,crimes [746] preparing,financially [722] #abiy,#isaias [632] genocide,#tigray [524] continue,bombarded [522] worldbank,antonellabassa3 [520] jorgedajani,wbg_ida [517] antonellabassa3,jorgedajani [513] bombarded,#imf Top Word Pairs in Tweet in G4:
[257] covid,19 [254] 19,pushed [254] 56,million [254] worldwide,india's [254] poverty,worldwide [254] share,56 [254] 2020,covid [254] 71,million [254] pushed,71 [254] india's,share Top Word Pairs in Tweet in G5:
[8] undppa,unocha [8] unicef_auoffice,unwomenafrica [8] igadsecretariat,sadc_news [8] unwomenafrica,undppa [8] unocha,afdb_group [8] sadc_news,auc_paps [8] auc_paps,unoau_ [8] afdb_group,unicefafrica [8] unoau_,asstsecstateaf [8] jumuiya,igadsecretariat Top Word Pairs in Tweet in G6:
[37] critical,thinking [37] build,critical [37] thinking,skills [37] skills,learn [37] write,maths [37] maths,build [37] struggle,write [37] child,read [37] learn,anything [37] read,struggle Top Word Pairs in Tweet in G7:
[19] climate,finance [19] food,fuel [17] know,more [17] world,bank [17] fuel,prices [16] bank,group [15] more,world [14] country,#climateanddevelopment [14] #climateanddevelopment,reports [14] reports,produced Top Word Pairs in Tweet in G8:
[22] #imf,#worldbank [20] world,bank [15] 世界的な景気後退リスク高まる,世銀総裁 [13] 世銀総裁,ｉｍｆ専務理事 [9] global,recession [7] imf,world [7] #worldbank,#imf [6] ர,க [6] க,ற [6] nirmala,sitharaman Top Word Pairs in Tweet in G9:
[16] worldbank,imfnews [12] security,domain [12] potus,joebiden's [12] annual,meetings [12] greatest,opportunity [12] outside,security [12] worldbank,offers [12] domain,overhauling [12] overhauling,worldbank [12] joebiden's,administration Top Word Pairs in Tweet in G10:
[9] million,people [8] people,#tigray [8] afewrkei,#tigraygenocide [8] extermination,million [8] isaias,afewrkei [6] #tigray,abiyahmedali [6] abiyahmedali,isaias [4] qatar,uae [4] statedept,asstsecstateaf [4] afdb_group,worldbank Top Replied-To in Entire Graph:
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Top Mentioned in Entire Graph:
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Top Tweeters in Entire Graph:
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Top Tweeters in G10: