The graph represents a network of 2,965 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 Monday, 13 September 2021 at 16:50 UTC.
The requested start date was Monday, 13 September 2021 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 13-day, 22-hour, 26-minute period from Monday, 30 August 2021 at 00:30 UTC to Sunday, 12 September 2021 at 22:56 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 : 2965
Unique Edges : 2593
Edges With Duplicates : 6484
Total Edges : 9077
Number of Edge Types : 5
Retweet : 2689
MentionsInRetweet : 4049
Tweet : 370
Mentions : 1824
Replies to : 145
Self-Loops : 387
Reciprocated Vertex Pair Ratio : 0.0173482032218092
Reciprocated Edge Ratio : 0.0341047503045067
Connected Components : 126
Single-Vertex Connected Components : 62
Maximum Vertices in a Connected Component : 2427
Maximum Edges in a Connected Component : 8239
Maximum Geodesic Distance (Diameter) : 8
Average Geodesic Distance : 3.275841
Graph Density : 0.000560520512592937
Modularity : 0.415918
NodeXL Version : 1.0.1.446
Data Import : The graph represents a network of 2,965 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 Monday, 13 September 2021 at 16:50 UTC.
The requested start date was Monday, 13 September 2021 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 13-day, 22-hour, 26-minute period from Monday, 30 August 2021 at 00:30 UTC to Sunday, 12 September 2021 at 22:56 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 : Betweenness Centrality
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[421] climate,change [242] action,plan [228] change,action [194] world,bank [158] group,climate [146] climate,action [127] worldbank,group [104] learn,more [100] worldbank,wto [95] #developmentpodcast,worldbank Top Word Pairs in Tweet in G1:
[174] climate,change [99] action,plan [98] change,action [83] group,climate [70] climate,action [67] learn,more [66] world,bank [59] worldbank,group [49] creating,challenges [46] #developmentpodcast,worldbank Top Word Pairs in Tweet in G2:
[138] climate,change [108] action,plan [98] change,action [98] worldbank,wto [93] vaccine,inequity [93] inequity,driving [93] driving,dangerous [93] dangerous,divergences [93] divergences,heads [93] heads,imf Top Word Pairs in Tweet in G3:
[7] climate,change [6] wef,worldbank [5] foxnews,wionews [5] wionews,ani [4] climate,finance [4] worldbank,wef [3] imfnews,worldbank [3] #fintech,firms [3] survey,global [3] complete,survey Top Word Pairs in Tweet in G4:
[60] interested,career [60] career,global [60] global,impact [60] impact,apply [57] young,professionals [54] world,bank [47] professionals,program [47] program,roles [47] roles,ifc_org [46] apply,world Top Word Pairs in Tweet in G5:
[31] steps,child [31] support,home [29] recovery,tracker [26] environment,books [24] global,#education [24] #education,recovery [24] tracker,johnshopkins [24] johnshopkins,unicef [24] unicef,worldbank [24] worldbank,captures Top Word Pairs in Tweet in G6:
[9] operationalizing,farmer [9] farmer,led [9] led,#irrigation [9] scale,design [9] design,interventions [8] held,virtual [8] virtual,forum [8] forum,operationalizing [8] #irrigation,development [8] development,scale Top Word Pairs in Tweet in G7:
[35] 10,17 [35] 17,#sdgs [35] #sdgs,considered [35] considered,high [35] high,impact [35] impact,energy [35] energy,mobility [35] mobility,nexus [35] nexus,opportunity [34] opportunity,implement Top Word Pairs in Tweet in G8:
[12] 10,17 [12] 17,#sdgs [12] #sdgs,considered [12] considered,high [12] high,impact [12] impact,energy [12] energy,mobility [12] mobility,nexus [12] nexus,opportunity [11] cyberattacks,affect Top Word Pairs in Tweet in G9:
[62] look,canada [62] canada,penalizing [62] penalizing,itself [62] itself,global [62] global,elite [62] elite,good [62] good,books [62] books,china [62] china,russia [62] russia,brazil Top Word Pairs in Tweet in G10:
[13] world,bank [6] climate,change [4] bank,group [4] air,healthy [3] million,people [3] covid,19 [3] global,economic [3] linkages,healthy [3] healthy,air [3] healthy,planet 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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