The graph represents a network of 3,755 Twitter users whose tweets in the requested range contained "#malaria", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 20 November 2019 at 22:20 UTC.
The requested start date was Tuesday, 19 November 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 13-day, 23-hour, 46-minute period from Tuesday, 05 November 2019 at 01:13 UTC to Tuesday, 19 November 2019 at 00:59 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 : 3755
Unique Edges : 6365
Edges With Duplicates : 2135
Total Edges : 8500
Number of Edge Types : 3
Mentions : 7565
Tweet : 844
Replies to : 91
Self-Loops : 844
Reciprocated Vertex Pair Ratio : 0.0288234367616948
Reciprocated Edge Ratio : 0.0560318432333129
Connected Components : 520
Single-Vertex Connected Components : 267
Maximum Vertices in a Connected Component : 2352
Maximum Edges in a Connected Component : 6771
Maximum Geodesic Distance (Diameter) : 14
Average Geodesic Distance : 5.248863
Graph Density : 0.000463384994753931
Modularity : 0.67811
NodeXL Version : 1.0.1.421
Data Import : The graph represents a network of 3,755 Twitter users whose tweets in the requested range contained "#malaria", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 20 November 2019 at 22:20 UTC.
The requested start date was Tuesday, 19 November 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 13-day, 23-hour, 46-minute period from Tuesday, 05 November 2019 at 01:13 UTC to Tuesday, 19 November 2019 at 00:59 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 : #malaria
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 : Followers
Top Domains
Top Word Pairs in Tweet in Entire Graph:
[900] ø,ù [605] ù,ø [479] #tb,#malaria [473] #aids,#tb [399] ù,ù [388] against,#aids [386] #stepupthefight,against [383] regsprecher,bmz_bund [380] contribution,globalfund [379] thank,chancellor Top Word Pairs in Tweet in G1:
[432] #aids,#tb [432] #tb,#malaria [383] regsprecher,bmz_bund [383] against,#aids [380] contribution,globalfund [379] thank,chancellor [379] chancellor,merkel [379] merkel,regsprecher [379] bmz_bund,increased [379] increased,contribution Top Word Pairs in Tweet in G2:
[123] pahowho,whoemro [86] medsformalaria,drtedros [83] drtedros,whoafro [83] whoafro,whosearo [83] whosearo,whowpro [83] whowpro,pahowho [83] whoemro,who_europe [83] who_europe,rminghui [83] rminghui,palonsomalaria [62] against,#malaria Top Word Pairs in Tweet in G3:
[77] ho,lab [66] hiring,ho [66] lab,columbiamed [66] columbiamed,#nyc [66] #nyc,seeking [66] seeking,innovative [66] innovative,resourceful [66] resourceful,postdocs [66] postdocs,join [66] join,using Top Word Pairs in Tweet in G4:
[147] à,à [25] #hiv,#malaria [16] advancing,science [16] science,strategic [16] strategic,collaborations [16] collaborations,#zika [16] #zika,#ebola [16] #ebola,#hiv [16] #malaria,#marburg [16] #marburg,govx Top Word Pairs in Tweet in G5:
[19] happy,#gisday [19] geographic,information [19] information,systems [15] astmh,#tropmed19 [13] usaid,used [13] used,geographic [13] systems,strengthen [13] strengthen,local [13] local,infrastructure [13] infrastructure,deliver Top Word Pairs in Tweet in G6:
[37] casos,#malaria [28] #dã,amalariaamã [28] amalariaamã,ricas [24] parã,sitos [23] #malaria,#paludismo [23] #paludismo,enfermedad [23] enfermedad,infecciosa [23] infecciosa,causada [23] transmitidos,picadura [23] picadura,mosquito Top Word Pairs in Tweet in G7:
[19] borne,diseases [16] 3rd,fr [15] very,burden [15] burden,#dengue [15] #dengue,fever [15] fever,aedes [15] aedes,borne [15] diseases,continue [15] continue,rising [15] rising,africa Top Word Pairs in Tweet in G8:
[31] deadly,parasite [31] parasite,'jumped' [31] 'jumped',gorilla [31] gorilla,humans [31] humans,phytoceuticalsi [31] phytoceuticalsi,rohinishah73 [31] rohinishah73,sminaev2015 [31] sminaev2015,stelle_lune [31] stelle_lune,815wrldtrvlr [30] _atanas_,deadly Top Word Pairs in Tweet in G9:
[888] ø,ù [595] ù,ø [397] ù,ù [352] ø,ø [196] ù,ùš [99] ø,ùˆø [99] ùˆ,ø [98] ù,øµø [98] ù,øªø [50] ùƒø,ù Top Word Pairs in Tweet in G10:
[12] #datasharingchat,ensure [12] ensure,sustainability [12] sustainability,legacy [12] legacy,#datasharing [12] #datasharing,iddo [12] iddo,using [12] using,#cdisc [12] #cdisc,standards [12] standards,#malaria [11] iddonews,#datasharingchat 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: