The graph represents a network of 9,407 Twitter users whose tweets in the requested range contained "public health", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Saturday, 09 April 2022 at 11:50 UTC.
The requested start date was Saturday, 09 April 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, 1-hour, 44-minute period from Tuesday, 05 April 2022 at 09:23 UTC to Thursday, 07 April 2022 at 11:07 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 : 9407
Unique Edges : 5210
Edges With Duplicates : 12433
Total Edges : 17643
Number of Edge Types : 5
Retweet : 5830
MentionsInRetweet : 7349
Replies to : 736
Mentions : 2205
Tweet : 1523
Self-Loops : 1551
Reciprocated Vertex Pair Ratio : 0.0110309278350515
Reciprocated Edge Ratio : 0.0218211481594779
Connected Components : 1635
Single-Vertex Connected Components : 501
Maximum Vertices in a Connected Component : 4489
Maximum Edges in a Connected Component : 10383
Maximum Geodesic Distance (Diameter) : 24
Average Geodesic Distance : 7.925741
Graph Density : 0.000110835799120009
Modularity : 0.57001
NodeXL Version : 1.0.1.449
Data Import : The graph represents a network of 9,407 Twitter users whose tweets in the requested range contained "public health", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Saturday, 09 April 2022 at 11:50 UTC.
The requested start date was Saturday, 09 April 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, 1-hour, 44-minute period from Tuesday, 05 April 2022 at 09:23 UTC to Thursday, 07 April 2022 at 11:07 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 : public health
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:
[3889] public,health [434] weâ,ve [312] health,measures [307] weâ,re [273] re,asking [271] asking,parents [271] parents,carers [271] carers,vigilant [271] vigilant,symptoms [271] symptoms,jaundice Top Word Pairs in Tweet in G1:
[357] public,health [46] covid,19 [44] health,day [44] world,health [35] àµ,ൠ[20] national,public [19] health,week [18] mental,health [16] health,care [13] public,service Top Word Pairs in Tweet in G2:
[246] breakingâ,cdcgov [246] cdcgov,allow [246] allow,infectious [246] infectious,#covid19 [246] #covid19,cases [246] cases,fly [246] fly,stop [246] stop,such [246] such,reportingâ [246] reportingâ,effective Top Word Pairs in Tweet in G3:
[213] health,secretary [206] shocking,level [206] level,rank [206] rank,dishonesty [206] dishonesty,health [206] secretary,sajidjavid [206] sajidjavid,repeating [206] repeating,outright [206] outright,barefaced [205] peterstefanovi2,shocking Top Word Pairs in Tweet in G4:
[293] public,health [45] mask,mandates [26] economic,cost [24] health,care [20] bring,back [19] health,officials [17] removing,mask [16] casesâ,sick [16] sick,kidsâ [16] kidsâ,hospitalizationsâ Top Word Pairs in Tweet in G5:
[221] public,health [93] virus,spreads [93] spreads,aerosols [93] aerosols,causes [93] causes,neurodegeneration [93] neurodegeneration,renal [93] renal,dysfunction [93] dysfunction,cardiovascular [93] cardiovascular,disease [92] dgurdasani1,virus Top Word Pairs in Tweet in G6:
[209] public,health [140] health,measures [140] weâ,ve [137] œgoing,back [137] back,normalâ [137] normalâ,abandoning [137] abandoning,public [137] measures,covid [137] covid,means [137] means,weâ Top Word Pairs in Tweet in G7:
[247] weâ,re [247] re,asking [247] asking,parents [247] parents,carers [247] carers,vigilant [247] vigilant,symptoms [247] symptoms,jaundice [247] jaundice,children [247] children,weâ [247] weâ,ve Top Word Pairs in Tweet in G8:
[175] funny,those [175] those,welcome [175] welcome,destruction [175] destruction,channel [175] channel,exactly [175] exactly,same [175] same,people [175] people,promoted [175] promoted,madness [174] brexit_sham,funny Top Word Pairs in Tweet in G9:
[174] hm,treasury [127] doctors,nurses [126] morning,doctors [126] nurses,healthcare [126] healthcare,workers [126] workers,blocked [126] blocked,hm [126] treasury,call [126] call,government [126] government,stop Top Word Pairs in Tweet in G10:
[167] pensions,benefits [167] rents,house [167] house,prices [166] eyeswideopen69,live [166] live,france [166] france,compared [166] compared,uk [166] uk,pensions [166] benefits,higher [166] higher,rents Top Replied-To in Entire Graph:
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Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Tweeters in Entire Graph:
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Top Tweeters in G10: