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#500kdeaths Twitter NodeXL SNA Map and Report for Tuesday, 23 February 2021 at 17:35 UTC (experimental version)
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From:
marc_smith
Uploaded on:
February 23, 2021
Short Description:
#500kdeaths via NodeXL https://bit.ly/3dGzRnw
@resistersis20
@meidasgraphics2
@margari_r
@mariashriver
@amck74407349
@potus
@hmr812
@stevebrant
@alxellt0308
@lipiroy

Top hashtags:
#500kdeaths
#covid19
#500kcoviddeaths
#covid
#onev1
#medicareforall

Description:
Description
The graph represents a network of 1,730 Twitter users whose recent tweets contained "#500kdeaths", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 18,000 tweets. The network was obtained from Twitter on Tuesday, 23 February 2021 at 17:36 UTC.

The tweets in the network were tweeted over the 7-day, 19-hour, 42-minute period from Monday, 15 February 2021 at 21:32 UTC to Tuesday, 23 February 2021 at 17:14 UTC.

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


Overall Graph Metrics
Vertices : 1730
Unique Edges : 1976
Edges With Duplicates : 188
Total Edges : 2164
Number of Edge Types : 5
Retweet : 1225
MentionsInRetweet : 167
Replies to : 193
Tweet : 400
Mentions : 179
Self-Loops : 410
Reciprocated Vertex Pair Ratio : 0.00236826524570752
Reciprocated Edge Ratio : 0.00472533963378618
Connected Components : 350
Single-Vertex Connected Components : 259
Maximum Vertices in a Connected Component : 1095
Maximum Edges in a Connected Component : 1431
Maximum Geodesic Distance (Diameter) : 14
Average Geodesic Distance : 4.110024
Graph Density : 0.000565999257815504
Modularity : 0.756584
NodeXL Version : 1.0.1.443
Data Import : The graph represents a network of 1,730 Twitter users whose recent tweets contained "#500kdeaths", or who were replied to or mentioned in those tweets, taken from a data set limited to a maximum of 18,000 tweets. The network was obtained from Twitter on Tuesday, 23 February 2021 at 17:36 UTC.

The tweets in the network were tweeted over the 7-day, 19-hour, 42-minute period from Monday, 15 February 2021 at 21:32 UTC to Tuesday, 23 February 2021 at 17:14 UTC.

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 : TwitterSearch
Graph Term : #500kdeaths
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 : In-Degree

Top Influencers: Top 10 Vertices, Ranked by Betweenness Centrality
Top URLs
Top URLs in Tweet in Entire Graph:
[58] https://twitter.com/cnn/status/1363970450381041665
[18] https://twitter.com/cspan/status/1363994995842236417
[17] https://twitter.com/potus/status/1363983909495705603
[16] https://twitter.com/laurie_garrett/status/1362543067597852674?s=21
[16] https://twitter.com/ifindkarma/status/1352410656935317505?s=21
[13] https://www.wsws.org/en/articles/2021/02/23/pers-f23.htm
[12] https://www.scientificamerican.com/article/nursing-home-workers-had-one-of-the-deadliest-jobs-of-2020/
[11] https://twitter.com/leorahorwitzmd/status/1364011085246984201
[8] https://www.rawstory.com/joe-biden-toll/
[6] https://twitter.com/latimes/status/1364233761857003524

Top URLs in Tweet in G2:
[2] https://www.washingtonpost.com/nation/interactive/2021/500000-covid-deaths-visualized/?no_nav=true&tid=a_classic-iphone
[2] https://twitter.com/danrather/status/1363609164124016646
[2] https://twitter.com/thedailyshow/status/1363911683723337731
[2] https://twitter.com/cspan/status/1363994995842236417
[2] https://www.nytimes.com/2021/02/22/us/us-covid-deaths-half-a-million.html
[2] https://eaworldview.com/2021/02/biden-people-we-lost-extraordinary/
[2] https://twitter.com/neal_katyal/status/1363988637667500037
[1] https://twitter.com/JYSexton/status/1363574140045647877
[1] https://www.nationalgeographic.com/science/graphics/what-500000-united-states-covid-deaths-look-like
[1] https://www.huffpost.com/entry/anthony-fauci-donald-trump-covid-19-conflict_n_602e780bc5b67c32961bc190

Top URLs in Tweet in G3:
[2] https://www.youtube.com/watch?v=KZn1yulnc1U&feature=youtu.be

[1] https://twitter.com/latimes/status/1364233761857003524
[1] https://twitter.com/cnn/status/1363970450381041665

Top URLs in Tweet in G4:
[16] https://twitter.com/cspan/status/1363994995842236417
[5] https://twitter.com/howardmortman/status/1364010193512759298
[1] https://www.rawstory.com/joe-biden-toll/
[1] https://twitter.com/msnbc/status/1364002647238467585
[1] https://www.youtube.com/watch?v=AFWWeSYWCkY&feature=youtu.be

[1] https://www.npr.org/2021/02/22/970155352/white-house-to-honor-victims-of-the-coronavirus-in-evening-ceremony
[1] https://twitter.com/POTUS/status/1363987244688629760
[1] https://twitter.com/FLOTUS/status/1363986941121757185
[1] https://twitter.com/Covid19WarRoom/status/1363892305799696386

Top URLs in Tweet in G5:
[51] https://twitter.com/cnn/status/1363970450381041665
[1] https://twitter.com/POTUS/status/1363983909495705603

Top URLs in Tweet in G6:
[11] https://twitter.com/leorahorwitzmd/status/1364011085246984201
[6] https://www.rawstory.com/joe-biden-toll/
[5] https://twitter.com/maiamajumder/status/1363997918152306689
[2] https://twitter.com/cnn/status/1363970450381041665
[1] https://thehill.com/policy/healthcare/539759-us-passes-grim-milestone-of-500000-coronavirus-deaths

Top URLs in Tweet in G9:
[3] https://www.nationalgeographic.com/science/graphics/what-500000-united-states-covid-deaths-look-like?loggedin=true
[1] https://twitter.com/cnn/status/1363970450381041665

Top Domains
Top Hashtags
Top Hashtags in Tweet in Entire Graph:
[1817] 500kdeaths
[276] covid19
[86] 500kcoviddeaths
[75] covid
[59] onev1
[49] medicareforall
[47] trumpliedpeopledied
[46] covidー19
[39] presidentbiden
[36] coronavirus



Top Hashtags in Tweet in G1:
[472] 500kdeaths
[2] covid
[2] coronavirus
[2] trumpvirus
[1] criminal

Top Hashtags in Tweet in G2:
[277] 500kdeaths
[63] covid19
[19] coronavirus
[19] 500kcoviddeaths
[14] covid
[14] covidー19
[13] trump
[12] wearamask
[9] biden
[7] covid_19

Top Hashtags in Tweet in G3:
[169] 500kdeaths
[35] covid
[33] trumpliedpeopledied
[30] presidentbiden
[25] covid19
[25] prayforamerica
[23] healthcareheroes
[7] donaldtrump
[7] healthcareforall
[7] staywoke

Top Hashtags in Tweet in G4:
[74] 500kdeaths
[13] covid19
[9] 500kcoviddeaths
[5] trump
[3] disgraceful
[3] republicansdontcare
[3] amazinggrace
[3] connecticut
[2] gopcowards
[2] liars

Top Hashtags in Tweet in G5:
[99] 500kdeaths

Top Hashtags in Tweet in G6:
[71] 500kdeaths
[32] covid19
[6] formerguy
[6] gqp
[3] weremember
[2] restinpeace
[1] covid
[1] trumpliedpeopledied
[1] onev1

Top Hashtags in Tweet in G7:
[50] 500kdeaths
[49] medicareforall
[2] forcethevote

Top Hashtags in Tweet in G8:
[54] 500kdeaths
[49] onev1

Top Hashtags in Tweet in G9:
[61] 500kdeaths
[8] covid19
[7] coronavirususa
[6] covidー19
[6] covidvaccine
[6] wearamask
[4] coronavirus
[4] pandemic
[2] update
[1] includingmymom

Top Hashtags in Tweet in G10:
[50] 500kdeaths
[1] covid
[1] trumpliedpeopledied
[1] potus

Top Words
Top Words in Tweet in Entire Graph:
[1817] #500kdeaths
[988] grave
[715] amp
[646] remember
[588] today
[580] life
[574] gone
[564] americans
[543] changed
[540] forever

Top Words in Tweet in G1:
[940] grave
[474] amp
[472] #500kdeaths
[470] miracle
[470] disapear
[470] warm
[470] weather
[470] end
[470] scourge
[470] beget

Top Words in Tweet in G2:
[277] #500kdeaths
[63] #covid19
[47] covid
[36] 000
[36] lost
[35] people
[34] 500
[27] president
[26] biden
[25] lives

Top Words in Tweet in G3:
[169] #500kdeaths
[66] 15
[51] thank
[49] trump
[48] 500k
[44] people
[37] death
[36] 000
[35] days
[35] #covid

Top Words in Tweet in G4:
[74] #500kdeaths
[47] potus
[13] amp
[13] thank
[13] #covid19
[12] 000
[9] ericholder
[9] #500kcoviddeaths
[9] 500
[8] loss

Top Words in Tweet in G5:
[189] 000
[108] much
[99] #500kdeaths
[88] remember
[87] 500
[72] number
[52] today
[52] gone
[51] approaching
[51] 100

Top Words in Tweet in G6:
[71] #500kdeaths
[55] ones
[52] loved
[44] 000
[41] lost
[40] 500
[36] harder
[32] #covid19
[31] more
[30] families

Top Words in Tweet in G7:
[50] #500kdeaths
[49] #medicareforall
[47] amazing
[47] grace
[2] repaoc
[2] #forcethevote

Top Words in Tweet in G8:
[54] #500kdeaths
[49] taken
[49] little
[49] competence
[49] spiral
[49] control
[49] instead
[49] 500k
[49] souls
[49] lost

Top Words in Tweet in G9:
[61] #500kdeaths
[39] 000
[37] 500
[36] never
[36] happen
[31] year
[24] lost
[24] war
[21] natgeo
[21] minute

Top Words in Tweet in G10:
[92] amp
[88] one
[50] #500kdeaths
[48] life
[48] forever
[48] changed
[45] death
[44] imagine
[44] emotional
[44] spiritual

Top Word Pairs
Top Word Pairs in Tweet in Entire Graph:
[496] today,remember
[495] tragedy,#500kdeaths
[495] gone,soon
[494] miracle,disapear
[494] disapear,warm
[494] warm,weather
[494] weather,end
[494] end,scourge
[494] scourge,beget
[494] beget,grave

Top Word Pairs in Tweet in G1:
[470] miracle,disapear
[470] disapear,warm
[470] warm,weather
[470] weather,end
[470] end,scourge
[470] scourge,beget
[470] beget,grave
[470] grave,grave
[470] grave,mothers
[470] mothers,buried

Top Word Pairs in Tweet in G2:
[30] 500,000
[21] #covid19,#500kdeaths
[18] #500kdeaths,#500kcoviddeaths
[16] half,million
[15] #500kdeaths,#covid19
[12] covid,19
[9] lives,lost
[7] loved,ones
[5] 000,dead
[5] made,cry

Top Word Pairs in Tweet in G3:
[33] 15,people
[33] people,15
[33] 15,within
[33] within,couple
[33] couple,days
[33] days,going
[33] going,down
[33] down,close
[33] close,zero
[33] zero,trump

Top Word Pairs in Tweet in G4:
[9] ericholder,#500kdeaths
[8] potus,#500kdeaths
[8] 500,000
[7] potus,vp
[6] thank,potus
[6] #500kdeaths,#500kcoviddeaths
[5] true,humanitarian
[5] humanitarian,patriot
[5] patriot,potus
[5] #covid19,#500kdeaths

Top Word Pairs in Tweet in G5:
[87] 500,000
[51] remember,approaching
[51] approaching,100
[51] 100,000
[51] 000,mark
[51] mark,couldn
[51] couldn,believe
[51] believe,bad
[51] bad,200
[51] 200,000

Top Word Pairs in Tweet in G6:
[52] loved,ones
[40] 500,000
[27] families,loved
[25] ones,500
[25] 000,mothers
[25] mothers,fathers
[25] fathers,daughters
[25] daughters,sons
[25] sons,sisters
[25] sisters,brothers

Top Word Pairs in Tweet in G7:
[47] #medicareforall,amazing
[47] amazing,grace
[47] grace,#500kdeaths
[2] repaoc,#forcethevote
[2] #forcethevote,#medicareforall
[2] #medicareforall,#500kdeaths

Top Word Pairs in Tweet in G8:
[49] taken,little
[49] little,competence
[49] competence,spiral
[49] spiral,control
[49] control,instead
[49] instead,500k
[49] 500k,souls
[49] souls,lost
[49] lost,many
[49] many,more

Top Word Pairs in Tweet in G9:
[37] 500,000
[21] minute,entire
[21] entire,year
[18] short,impactful
[18] impactful,perspective
[18] perspective,many
[18] many,500
[18] 000,truly
[18] truly,natgeo
[18] natgeo,sitting

Top Word Pairs in Tweet in G10:
[44] imagine,emotional
[44] emotional,spiritual
[44] spiritual,amp
[44] amp,physical
[44] physical,pain
[44] pain,compelled
[44] compelled,leave
[44] leave,world
[44] world,one
[44] one,death

Top Replied-To
Top Replied-To in Entire Graph:
@kaitlancollins
@acosta
@potus
@ericholder
@alifeofinsanity
@brikeilarcnn
@atrupar
@repadamschiff
@donaldjtrumpjr
@nbcnews

Top Replied-To in G1:
@stevenbeschloss
@resistersis20

Top Replied-To in G3:
@kaitlancollins
@acosta
@alifeofinsanity
@brikeilarcnn
@atrupar
@repadamschiff
@therecount
@brianstelter
@kellabel
@mysterysolvent

Top Replied-To in G4:
@potus
@ericholder
@nbcnews
@repdanbishop
@caslernoel
@slate
@vp
@mehdirhasan
@danrather
@retreado

Top Replied-To in G6:
@npr

Top Replied-To in G7:
@repaoc
@norahodonnell

Top Mentioned
Top Mentioned in Entire Graph:
@potus
@joebiden
@natgeo
@tanyalewis314
@unamandita
@sciam
@leorahorwitzmd
@whitehouse
@brikeilarcnn
@jakelobin

Top Mentioned in G2:
@charlote_crypto

Top Mentioned in G3:
@brikeilarcnn
@jakelobin
@cnn
@jaketapper
@56blackcat
@larry_kudlow
@thedailyshow
@drsanjaygupta
@youtube
@ricosuavejd

Top Mentioned in G4:
@potus
@vp
@sentomcotton
@ummismaelsf
@govnedlamont
@shellcamg
@hhsgov
@urocklive1
@whitehouse
@statedept

Top Mentioned in G6:
@leorahorwitzmd
@natgeo

Top Mentioned in G9:
@natgeo
@whitehouse

Top Tweeters
Top Tweeters in Entire Graph:
@missb62
@dichristine
@lucioquincioc
@teshawnedmonds
@7b73f39b85e1415
@joni_looking
@homegypsy
@kenkircher1
@chrisbrey1
@padakitty

Top Tweeters in G1:
@teshawnedmonds
@homegypsy
@iflck
@cotey_mary
@manchuriandevil
@carlyinnj
@girlzinger
@straitarrow10
@aclaysuper
@fran_neena20409

Top Tweeters in G2:
@padakitty
@mtnbvan
@tbluvoter
@katedmiston
@sassybibrarian
@specneedsmom4
@yogaskidogs
@scottlucas_ea
@sherrypcmo
@tradledee85

Top Tweeters in G3:
@joni_looking
@chrisbrey1
@spencz1997
@cnn
@reeniegeraci
@borrelligerlach
@debp197
@msnbc
@jaketapper
@56blackcat

Top Tweeters in G4:
@slate
@way2gosassy
@ckkoch3
@sundene
@urocklive1
@medit8now
@nbcnews
@abirish
@funder
@heinslerjan

Top Tweeters in G5:
@7b73f39b85e1415
@aliadair22
@wcaddict
@lonestarmomcom
@anniesage
@belladonamodels
@cookkcegyptian
@kcgreen17
@tampaefl
@kingmikebeon

Top Tweeters in G6:
@elkehollings
@now_justice
@tomvarghesejr
@rebeccamccoyb1
@npr
@abreen29364489
@deaschroeder
@famcat
@kelhuntslight
@scottshusband

Top Tweeters in G7:
@brendahazelhur1
@pppatticake
@pauljimerson
@wavesofeuphoria
@georgiemutt
@lmorihouse
@osiris322
@laserhaas01
@hotleadenema
@wilson6923

Top Tweeters in G8:
@debsomewhere
@maddiebarry8
@johnny_queer
@alxellt0308
@mautarsha1
@hig68
@theresec55
@joe_blue61
@laura_hbic
@papootx

Top Tweeters in G9:
@missb62
@lucioquincioc
@nancyrubin
@drdind
@pamunplugged
@msactiviss
@stabbytosavit
@schmoopywoopy
@sfutorian
@jomareewade

Top Tweeters in G10:
@missnisha6849
@lizditz
@meidas_damon
@brontyman
@njdoc
@maine_char
@hlthiskrieger
@maryjan62216031
@joyrosem
@brokenbong


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