The graph represents a network of 5,835 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, 12 December 2019 at 17:56 UTC.
The requested start date was Thursday, 12 December 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 2-day, 1-hour, 27-minute period from Monday, 09 December 2019 at 23:33 UTC to Thursday, 12 December 2019 at 01:01 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 : 5835
Unique Edges : 8569
Edges With Duplicates : 12177
Total Edges : 20746
Number of Edge Types : 3
Replies to : 647
Mentions : 19639
Tweet : 460
Self-Loops : 460
Reciprocated Vertex Pair Ratio : 0.0144830232112028
Reciprocated Edge Ratio : 0.0285525196180391
Connected Components : 236
Single-Vertex Connected Components : 119
Maximum Vertices in a Connected Component : 5105
Maximum Edges in a Connected Component : 19929
Maximum Geodesic Distance (Diameter) : 13
Average Geodesic Distance : 4.047862
Graph Density : 0.000310709991572025
Modularity : 0.426917
NodeXL Version : 1.0.1.422
Data Import : The graph represents a network of 5,835 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, 12 December 2019 at 17:56 UTC.
The requested start date was Thursday, 12 December 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 2-day, 1-hour, 27-minute period from Monday, 09 December 2019 at 23:33 UTC to Thursday, 12 December 2019 at 01:01 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:
[225] world,bank [159] freedom,fighters [157] fellow,freedom [157] fighters,sen [157] sen,chuckgrassley [157] chuckgrassley,chairman [157] chairman,senate [157] senate,finance [157] finance,cmte [157] cmte,controls Top Word Pairs in Tweet in G1:
[51] extreme,poverty [48] #water,life [48] life,little [48] little,survive [48] survive,much [48] much,deadly [48] deadly,#climatechange [48] #climatechange,increasing [48] increasing,droughts [48] droughts,floods Top Word Pairs in Tweet in G2:
[30] vdombrovskis,nadiacalvino [22] imfnews,worldbank [21] axelvt_wb,worldbank [21] wef,worldbank [20] nadiacalvino,eib [19] worldbank,group [19] sustainable,finance [18] worldbank,imfnews [18] world,bank [18] worldbank,glmforum Top Word Pairs in Tweet in G3:
[32] reach,full [22] worldbank,report [19] proposals,reform [18] virtual,conference [18] g24,oecd [17] #southasia,bounce [17] bounce,back [17] back,economic [17] economic,downturn [17] downturn,reach Top Word Pairs in Tweet in G4:
[158] freedom,fighters [157] fellow,freedom [157] fighters,sen [157] sen,chuckgrassley [157] chuckgrassley,chairman [157] chairman,senate [157] senate,finance [157] finance,cmte [157] cmte,controls [157] controls,purse Top Word Pairs in Tweet in G5:
[88] pmoindiamodi,rbi [88] rbi,finminindia [88] finminindia,nsitharaman [88] nsitharaman,fayedsouza [88] abpnews,mumbaimirror [88] mumbaimirror,mirrornow [88] mirrornow,httweets [74] agrigoi,nstomar [73] fayedsouza,#pmcbankcrisis [73] #pmcbankcrisis,abpnews Top Word Pairs in Tweet in G6:
[148] 中国共産党がworldbankを買収しようとしている状況だし,国賓としては呼ばない方がいいです [148] 国賓としては呼ばない方がいいです,日本銀行の上に [148] 日本銀行の上に,中国共産党資本が付いたら国民完全管理 [148] 中国共産党資本が付いたら国民完全管理,臓器売買ビジネス思想へ行きますぞ [148] 臓器売買ビジネス思想へ行きますぞ,日本は独立すべきです [147] junsakura_japan,中国共産党がworldbankを買収しようとしている状況だし [46] トランプ大統領,中国への融資の中止を世界銀行へ投げかけ [45] junsakura_japan,トランプ大統領 [3] emit_0710q,世界銀行は公式 [3] 世界銀行は公式,あ Top Word Pairs in Tweet in G7:
[31] learning,crisis [28] affordable,housing [28] housing,policy [27] crisis,silent [27] silent,crisis [27] crisis,solving [27] solving,needs [27] needs,focus [27] focus,persistence [27] persistence,requires Top Word Pairs in Tweet in G8:
[89] cstterryparmar,deputychiefrai [89] deputychiefrai,terryyungyvr [89] terryyungyvr,vpdsgtmajor [89] vpdsgtmajor,sergeantvance [89] sergeantvance,ee1475 [89] ee1475,damianvpd [89] damianvpd,duncan1557 [87] duncan1557,1507andersen [87] 1507andersen,fionawilsonvpd [87] fionawilsonvpd,chiefpalmer Top Word Pairs in Tweet in G9:
[54] podcast,best [54] best,ways [54] ways,reduce [54] reduce,#poverty [54] #poverty,#africa [54] #africa,hear [54] hear,more [54] more,experts [54] experts,kathleen [54] kathleen,beegle Top Word Pairs in Tweet in G10:
[5] health,outcomes [5] outcomes,produced [5] produced,within [5] within,health [5] health,systems [5] systems,community [5] community,education [5] education,systems [5] systems,essential' [4] golichenko,'only Top Replied-To in Entire Graph:
Top Replied-To in G1:
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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: