(immigrant OR immigration) (COVID OR corona OR virus OR pandemic OR ill OR illness OR health OR doctor OR nurse), Twitter, 3/15/2023 11:19:54 PM, 291301


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(immigrant OR immigration) (COVID OR corona OR virus OR pandemic OR ill OR illness OR health OR doct
(immigrant OR immigration) (COVID OR corona OR virus OR pandemic OR ill OR illness OR health OR doct
From:
NodeXLExcelAutomator
Uploaded on:
March 15, 2023
Short Description:
(immigrant OR immigration) (COVID OR corona OR virus OR pandemic OR ill OR illness OR health OR doctor OR nurse) via NodeXL https://bit.ly/3yIeOdy
@russincheshire
@garylineker
@mancunianmedic
@laverty_bryan
@doctor_oxford
@andrewlbyrne
@marcuschown
@louisagummer
@zoejardiniere
@conservativ

Description:
Description
The graph represents a network of 6,445 Twitter users whose recent tweets contained "(immigrant OR immigration) (COVID OR corona OR virus OR pandemic OR ill OR illness OR health OR doctor OR nurse)", or who were replied to, mentioned, retweeted or quoted in those tweets, taken from a data set limited to a maximum of 5,000 tweets, tweeted between 3/26/2006 12:00:00 AM and 3/14/2023 5:00:36 PM. The network was obtained from Twitter on Wednesday, 15 March 2023 at 23:11 UTC.

The tweets in the network were tweeted over the 1845-day, 8-hour, 10-minute period from Friday, 23 February 2018 at 15:47 UTC to Tuesday, 14 March 2023 at 23:58 UTC.

There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, an edge for each "retweet" relationship in a tweet, an edge for each "quote" relationship in a tweet, an edge for each "mention in retweet" relationship in a tweet, an edge for each "mention in reply-to" relationship in a tweet, an edge for each "mention in quote" relationship in a tweet, an edge for each "mention in quote reply-to" relationship in a tweet, and a self-loop edge for each tweet that is not from above.

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 : 6445
Unique Edges : 3399
Edges With Duplicates : 10415
Total Edges : 13814
Number of Edge Types : 9
Replies to : 1485
MentionsInReplyTo : 3095
Tweet : 692
Retweet : 3548
MentionsInRetweet : 4475
Mentions : 361
MentionsInQuote : 37
Quote : 87
MentionsInQuoteReply : 34
Self-Loops : 947
Reciprocated Vertex Pair Ratio : 0.0330245670559807
Reciprocated Edge Ratio : 0.0639376218323587
Connected Components : 878
Single-Vertex Connected Components : 225
Maximum Vertices in a Connected Component : 2287
Maximum Edges in a Connected Component : 5548
Maximum Geodesic Distance (Diameter) : 14
Average Geodesic Distance : 4.821957
Graph Density : 0.000185280694835111
Modularity : 0.545746
NodeXL Version : 1.0.1.510
Data Import : The graph represents a network of 6,445 Twitter users whose recent tweets contained "(immigrant OR immigration) (COVID OR corona OR virus OR pandemic OR ill OR illness OR health OR doctor OR nurse)", or who were replied to, mentioned, retweeted or quoted in those tweets, taken from a data set limited to a maximum of 5,000 tweets, tweeted between 3/26/2006 12:00:00 AM and 3/14/2023 5:00:36 PM. The network was obtained from Twitter on Wednesday, 15 March 2023 at 23:11 UTC.

The tweets in the network were tweeted over the 1845-day, 8-hour, 10-minute period from Friday, 23 February 2018 at 15:47 UTC to Tuesday, 14 March 2023 at 23:58 UTC.

There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, an edge for each "retweet" relationship in a tweet, an edge for each "quote" relationship in a tweet, an edge for each "mention in retweet" relationship in a tweet, an edge for each "mention in reply-to" relationship in a tweet, an edge for each "mention in quote" relationship in a tweet, an edge for each "mention in quote reply-to" relationship in a tweet, and a self-loop edge for each tweet that is not from above.

Layout Algorithm : The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.
Graph Source : TwitterSearch2
Graph Term : (immigrant OR immigration) (COVID OR corona OR virus OR pandemic OR ill OR illness OR health OR doctor OR nurse)
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 Influencers: Top 10 Vertices, Ranked by Betweenness Centrality
Top URLs
Top URLs in Tweet in Entire Graph:
[867] https://migrationobservatory.ox.ac.uk/resources/briefings/migrants-in-the-uk-an-overview/
[153] https://www.breitbart.com/immigration/2023/03/10/report-illegal-migration-costs-american-health-system-least-23-billion-per-year/
[29] https://twitter.com/brontyman/status/1635060537473245184/photo/1
[27] https://cis.org/Richwine/States-Must-Pay-Health-and-Education-Benefits-Illegal-Immigrant-Families
[18] https://www.numbersusa.com/blog/nurse-alleges-indentured-servitude-legal-immigration-system
[14] https://twitter.com/NumbersUSA/status/1634568452126957570/photo/1
[12] https://migrationobservatory.ox.ac.uk/resources/brie
[10] https://www.mdpi.com/2673-8112/2/12/121#
[9] https://www.justice.gov/opa/pr/associate-attorney-general-vanita-gupta-issues-statement-fbi-s-supplemental-2021-hate-crime
[8] http://www.mcgrawcenter.org/the-harold-w-mcgraw-jr-business-journalism-fellowships/

Top URLs in Tweet in G1:
[806] https://migrationobservatory.ox.ac.uk/resources/briefings/migrants-in-the-uk-an-overview/
[1] https://www.ucl.ac.uk/economics/about-department/fiscal-effects-immigration-uk
[1] https://www.oxfordeconomics.com/resource/the-fiscal-impact-of-immigration-on-the-uk/
[1] https://fullfact.org/health/foreign-born-nhs-eu/
[1] https://twitter.com/susanchubb1/status/1444209646244442117

Top URLs in Tweet in G2:
[1] https://100percentfedup.com/bidens-new-budget-requests-billions-to-help-usher-more-illegal-immigrants-in-paltry-increase-for-border-security/
[1] https://twitter.com/i/web/status/1635260024309030915
[1] https://twitter.com/RNCResearch/status/1633898725742395406
[1] https://www.youtube.com/watch?app=desktop&v=lNtbjnUrwO4
[1] https://twitter.com/RNCResearch/status/1633898725742395406/video/1

Top URLs in Tweet in G3:
[4] https://twitter.com/DaveAtherton20/status/1634507302936911872/photo/1
[4] https://twitter.com/LoverSeani/status/1634574912802242564/photo/1
[1] https://twitter.com/jeremycorbyn/status/1634578081619886088/photo/1
[1] https://twitter.com/jeremycorbyn/status/1635233877211115521/photo/1
[1] https://twitter.com/i/web/status/1633589702178504714
[1] https://twitter.com/TalkTV/status/1635409359642451968/video/1
[1] https://twitter.com/TalkTV/status/1635545554477277185/video/1
[1] https://twitter.com/KEdge23/status/1634634411344900097/photo/1
[1] https://twitter.com/KEdge23/status/1634711141401219073/photo/1
[1] https://twitter.com/danielbilling/status/1635238862774755330/photo/1

Top URLs in Tweet in G4:
[46] https://www.breitbart.com/immigration/2023/03/10/report-illegal-migration-costs-american-health-system-least-23-billion-per-year/
[3] https://www.numbersusa.com/blog/nurse-alleges-indentured-servitude-legal-immigration-system
[3] https://twinybots.ch/
[2] https://www.easyexpat.com/en/mag/2023/03/12/new-visa-rules-to-draw-expats-to-singapore.htm
[2] https://twitter.com/natashakorecki/status/1634210674476740611/photo/1
[2] https://twitter.com/johnworldpeace/status/1634690913107836929/photo/1
[1] https://www.youtube.com/watch?v=8zbhxYDXlo4

[1] https://www.cnn.com/2023/02/07/politics/title-42-biden-administration-public-health-emergency-expire/index.html
[1] https://www.pbs.org/newshour/politics/biden-administration-to-limit-asylum-to-migrants-who-pass-through-a-3rd-nation
[1] https://twitter.com/BradShowLive/status/1634346036641538049/video/1

Top URLs in Tweet in G5:
[29] https://twitter.com/brontyman/status/1635060537473245184/photo/1
[2] https://twitter.com/factandrumor/status/1620514909032448004/photo/1

Top URLs in Tweet in G6:
[12] https://migrationobservatory.ox.ac.uk/resources/briefings/migrants-in-the-uk-an-overview/
[2] https://twitter.com/jdpoc/status/1635265016382509057/photo/1

Top URLs in Tweet in G7:
[1] https://twitter.com/fentyheat/status/1635000760818864129

Top URLs in Tweet in G8:
[16] https://migrationobservatory.ox.ac.uk/resources/briefings/migrants-in-the-uk-an-overview/
[1] https://twitter.com/marcuschown/status/1634590330577207297/photo/1
[1] https://twitter.com/marcuschown/status/1634566326776725504/photo/1
[1] https://twitter.com/marcuschown/status/1634600253105029130/photo/1

Top URLs in Tweet in G9:
[27] https://cis.org/Richwine/States-Must-Pay-Health-and-Education-Benefits-Illegal-Immigrant-Families
[9] https://www.justice.gov/opa/pr/associate-attorney-general-vanita-gupta-issues-statement-fbi-s-supplemental-2021-hate-crime
[4] https://twitter.com/Ilhan/status/1635390813940375554/photo/1
[2] https://twitter.com/joemill37087868/status/1635304911939223552/photo/1
[1] https://twitter.com/AssholeEddie3/status/1634350278408380416/photo/1
[1] https://twitter.com/political_dheu/status/1634352533530607616/photo/1
[1] https://twitter.com/POTUS/status/1634218814358315008/photo/1
[1] https://twitter.com/POTUS/status/1634373585656578055/photo/1
[1] https://twitter.com/JoeBiden/status/1634562347799814144/photo/1
[1] https://twitter.com/CalltoActivism/status/1634645849169903619

Top URLs in Tweet in G10:
[13] https://migrationobservatory.ox.ac.uk/resources/briefings/migrants-in-the-uk-an-overview/
[1] https://www.dailymail.co.uk/news/article-1242076/Cameron-Ill-cut-immigration-75-cent.html
[1] https://twitter.com/DanielaNadj/status/1634690029816561666

Top Domains
Top Domains in Tweet in Entire Graph:
[883] ac.uk
[716] twitter.com
[155] breitbart.com
[36] co.uk
[27] cis.org
[18] numbersusa.com
[13] youtube.com
[10] mdpi.com
[9] justice.gov
[8] mcgrawcenter.org

Top Domains in Tweet in G1:
[807] ac.uk
[1] oxfordeconomics.com
[1] fullfact.org
[1] twitter.com

Top Domains in Tweet in G2:
[3] twitter.com
[1] 100percentfedup.com
[1] youtube.com

Top Domains in Tweet in G3:
[37] twitter.com
[3] co.uk
[1] sky.com
[1] fullfact.org
[1] org.uk
[1] thejc.com
[1] theguardian.com

Top Domains in Tweet in G4:
[47] breitbart.com
[44] twitter.com
[3] numbersusa.com
[3] cvsoci.al
[3] p2a.co
[3] twinybots.ch
[3] cliffordribner.com
[2] easyexpat.com
[2] youtube.com
[2] co.nz

Top Domains in Tweet in G5:
[31] twitter.com

Top Domains in Tweet in G6:
[12] ac.uk
[2] twitter.com

Top Domains in Tweet in G7:
[1] twitter.com

Top Domains in Tweet in G8:
[16] ac.uk
[3] twitter.com

Top Domains in Tweet in G9:
[67] twitter.com
[27] cis.org
[9] justice.gov
[3] hhs.gov
[2] nypost.com
[1] prisonpolicy.org
[1] aclj.org
[1] suncommunitynews.com
[1] eventbrite.com
[1] apnews.com

Top Domains in Tweet in G10:
[13] ac.uk
[1] co.uk
[1] twitter.com

Top Hashtags
Top Hashtags in Tweet in Entire Graph:
[30] fyi
[23] covid
[23] truestory
[20] immigration
[14] covid19
[9] ukraine
[9] journalism
[8] brexit
[8] coverage4all
[7] health



Top Hashtags in Tweet in G3:
[2] tories
[1] neverlabour
[1] doctorwho
[1] stoph1bnow
[1] h1b
[1] layoffs
[1] lottery
[1] illegalmigrationbill
[1] motd
[1] bustedflush

Top Hashtags in Tweet in G4:
[10] immigration
[9] covid
[4] biden
[4] health
[3] visa
[3] coverage4all
[3] energy
[3] hunterbiden
[3] laptop
[3] msm

Top Hashtags in Tweet in G5:
[1] demvoice1
[1] wtpblue
[1] dems4rights

Top Hashtags in Tweet in G8:
[2] sosnhsdemo

Top Hashtags in Tweet in G9:
[1] abolition
[1] communitiesnotcages
[1] mondaymotivation
[1] womenshistorymonth
[1] sxsw
[1] ncpol
[1] teamnerd
[1] donksfriends
[1] democratsdeliver
[1] aanhpicommission

Top Hashtags in Tweet in G10:
[1] smallboats

Top Words
Top Words in Tweet in Entire Graph:
[2086] nhs
[1770] immigration
[1182] health
[1099] uk
[978] immigrants
[941] population
[900] doctors
[894] born
[889] 14
[889] overseas

Top Words in Tweet in G1:
[1613] nhs
[810] immigrants
[810] russincheshire
[808] 28
[808] uk
[808] born
[807] population
[807] overseas
[807] 14
[806] swamp

Top Words in Tweet in G2:
[301] biden
[288] gas
[287] health
[287] nightmares
[286] daddy
[286] mandates
[286] control
[286] lives
[286] over
[286] government

Top Words in Tweet in G3:
[101] garylineker
[96] immigration
[58] people
[51] health
[31] re
[27] bbc
[27] covid
[25] saying
[21] uk
[20] care

Top Words in Tweet in G4:
[134] immigration
[122] health
[56] illegal
[50] covid
[44] system
[40] costs
[38] billion
[36] 23
[36] people
[36] american

Top Words in Tweet in G5:
[417] doctor
[223] biden
[194] dr
[194] kelly
[194] jill
[194] education
[194] brigitte
[194] question
[194] megyn
[194] referred

Top Words in Tweet in G6:
[155] retired
[155] middlesbrough
[155] teacher
[155] holiday
[155] nurse
[155] lanzarote
[155] couple
[155] chatting
[155] february
[154] th

Top Words in Tweet in G7:
[224] black
[220] pregnant
[220] night
[220] house
[220] resting
[220] home
[220] mother
[220] ve
[220] immigrant
[132] uwitmeorwhat

Top Words in Tweet in G8:
[175] nhs
[166] more
[165] re
[162] marcuschown
[141] much
[140] lineker
[140] fund
[140] stop
[140] london
[140] gary

Top Words in Tweet in G9:
[63] immigration
[36] covid
[35] record
[33] potus
[27] harassment
[23] pandemic
[22] inflation
[22] illegal
[22] trump
[21] people

Top Words in Tweet in G10:
[139] immigration
[137] decisions
[137] numbers
[137] cuts
[137] cut
[137] mancunianmedic
[137] serial
[137] deliberate
[137] cause
[137] grants

Top Word Pairs
Top Word Pairs in Tweet in Entire Graph:
[881] born,overseas
[880] uk,population
[879] 28,nhs
[879] nhs,doctors
[878] overseas,28
[878] 14,uk
[878] population,born
[867] nhs,14
[866] immigrants,swamp
[866] swamp,nhs

Top Word Pairs in Tweet in G1:
[807] born,overseas
[806] nhs,doctors
[806] population,born
[806] overseas,28
[806] swamp,nhs
[806] immigrants,swamp
[806] nhs,14
[806] uk,population
[806] 14,uk
[806] 28,nhs

Top Word Pairs in Tweet in G2:
[286] nightmares,government
[286] lives,health
[286] mandates,gas
[286] aspect,lives
[286] government,daddy
[286] daddy,control
[286] two,years
[286] over,aspect
[286] biden,nightmares
[286] control,over

Top Word Pairs in Tweet in G3:
[19] people,antivaxxers
[19] straight,labelling
[19] spreading,disease
[19] labelling,people
[19] re,spreading
[19] saying,re
[19] antivaxxers,saying
[16] disease,segregating
[14] segregating,soci
[14] deadferrets,straight

Top Word Pairs in Tweet in G4:
[36] 23,billion
[36] health,system
[35] system,23
[34] american,health
[34] costs,american
[27] billion,year
[25] migration,costs
[25] illegal,migration
[22] report,illegal
[17] health,care

Top Word Pairs in Tweet in G5:
[194] megyn,kelly
[194] dr,jill
[194] brigitte,gabriel
[194] gabriel,megyn
[194] doctor,education
[194] referred,doctor
[194] question,dr
[194] jill,biden
[194] doctor,doctor
[194] biden,referred

Top Word Pairs in Tweet in G6:
[155] chatting,couple
[155] february,chatting
[155] lanzarote,february
[155] retired,teacher
[155] holiday,lanzarote
[155] teacher,nurse
[155] middlesbrough,retired
[155] couple,middlesbrough
[154] nurse,th
[154] laverty_bryan,holiday

Top Word Pairs in Tweet in G7:
[220] home,resting
[220] house,night
[220] immigrant,black
[220] pregnant,immigrant
[220] black,mother
[220] mother,house
[220] ve,home
[220] night,ve
[132] uwitmeorwhat,pregnant
[79] fentyheat,pregnant

Top Word Pairs in Tweet in G8:
[165] re,more
[140] london,re
[140] much,solidarity
[140] fund,nhs
[140] nhs,stop
[140] gary,lineker
[140] stop,privatisation
[140] privatisation,march
[140] march,london
[140] solidarity,gary

Top Word Pairs in Tweet in G9:
[18] illegal,immigration
[12] immigration,detention
[12] covid,19
[9] facts,sheets
[9] students,discrimination
[9] education,issuing
[9] including,harassment
[9] discrimination,based
[9] national,origin
[9] origin,immigration

Top Word Pairs in Tweet in G10:
[137] cut,hospital
[137] bed,numbers
[137] support,grants
[137] numbers,cuts
[137] cuts,support
[137] immigration,cause
[137] serial,decisions
[137] decisions,cut
[137] cause,deliberate
[137] deliberate,serial

Top Replied-To
Top Replied-To in Entire Graph:
@doctor_oxford
@garylineker
@potus
@foxnews
@gbnews
@jeremycorbyn
@lbc
@scarfer13
@gop
@jenny_1884

Top Replied-To in G1:
@russincheshire
@natterblog
@sonnet_lumiere
@sacricketlover1
@brakespear1154
@euronews
@esther29611814

Top Replied-To in G2:
@aaronspeer10
@lisamikolajczy3
@miteacher1993
@jacemetzner

Top Replied-To in G3:
@garylineker
@jeremycorbyn
@kedge23
@baskerville_13
@carolvorders
@misspaulalondon
@juliahb1
@goldenkaos
@benirvineauthor
@dankandstein

Top Replied-To in G8:
@koraki_okeeffe
@maxrushden
@davegraham1975
@tomfletch30
@leegooner123

Top Replied-To in G9:
@potus
@nikkifried
@repjeffries
@donaldjtrumpjr
@repswalwell
@elisestefanik
@repstefanik
@meidastouch
@aaronparnas
@teampelosi

Top Replied-To in G10:
@neuro_matt
@mancunianmedic
@counsellingsam

Top Mentioned
Top Mentioned in Entire Graph:
@russincheshire
@toscaausten
@factandrumor
@marcuschown
@laverty_bryan
@mancunianmedic
@uwitmeorwhat
@garylineker
@drwaheedarian
@fentyheat

Top Mentioned in G1:
@russincheshire
@georgeupstairs
@sacricketlover1
@euronews

Top Mentioned in G2:
@toscaausten
@thehelpertoo
@rncresearch
@lngbch_hwn
@borgstromjames
@miteacher1993

Top Mentioned in G3:
@garylineker
@deadferrets
@juliahb1
@elonmusk
@secrettory12
@bbc
@a_webb
@clarkemicah
@talktv
@kedge23

Top Mentioned in G4:
@cliffordribner
@mhresearchunisa
@gregmerrick1
@xtremevg
@joeblow16872945

Top Mentioned in G5:
@factandrumor
@brontyman

Top Mentioned in G6:
@laverty_bryan
@jdpoc
@russincheshire
@mancunianmedic
@drwaheedarian

Top Mentioned in G7:
@uwitmeorwhat
@fentyheat
@deluxeefenty

Top Mentioned in G8:
@marcuschown
@russincheshire
@zoejardiniere
@philbear04
@layla_2468
@bakerstweet
@talksport
@mcardletrevor
@tomfletch30
@robb13jh

Top Mentioned in G9:
@potus
@joebiden
@stacysuh
@aaronparnas
@janettekirchner
@presssec
@dunkindona
@thedemocrats
@donaldjtrumpjr
@repswalwell

Top Mentioned in G10:
@mancunianmedic
@russincheshire
@marcuschown
@laverty_bryan
@drwaheedarian

Top Tweeters
Top Tweeters in Entire Graph:
@chidambara09
@hrblock_21
@roblwilson
@sandradunn1955
@sddphoto
@lyndae222
@madanabhat
@thehill
@carmillalusta
@katcapps

Top Tweeters in G1:
@ambiimoore
@mckinlay_liz
@fiona_fionnagal
@hausofrushdi
@vespasian91
@forumeditor
@kevinpbreslin
@jackalsbynight
@peradventur3
@susanchubb1

Top Tweeters in G2:
@saveaslave
@nahbabynah
@dianachic1
@vebo1991
@lgcomin
@annaapp91838450
@aukletqd
@katyinindy
@jver2me
@toscaausten

Top Tweeters in G3:
@bbcsport
@andyhammers
@mauriceg88
@cromwellstuff
@peterba82304711
@iromg
@dijolliffe
@revrichardcoles
@clarkemicah
@matthewjshow

Top Tweeters in G4:
@economictimes
@careerage
@mondaq
@silverkait
@kristekline
@gorbalsgoebbels
@julia_doughty
@mhdude1mhdude1
@dave1agar
@ursulav

Top Tweeters in G5:
@sddphoto
@katcapps
@brontyman
@cblazblaz
@brendaperrott
@frackhazreveal
@vmbritsch
@wismiss3
@stanspak
@bmlewis2

Top Tweeters in G6:
@tartancobweb
@ferguson2811
@xraypat
@markrowantree
@heather63262308
@david96212152
@safarisara
@matilda_w_
@maureenpickeri5
@tristramwyatt

Top Tweeters in G7:
@carmillalusta
@tylaskan
@the3jsmom
@mrmouthalmighty
@imma_gene_us
@adrianalrb
@iamtheflyest
@marssailor_
@anydamnways
@losttintheworld

Top Tweeters in G8:
@curiocat13
@spanishdan1
@chiller
@davidheadviews
@xpatjock
@voltuan
@vjl2
@mlvalentino1
@philrandal
@chrismaslanka

Top Tweeters in G9:
@sylviaz1913
@memeburk
@prison_health
@ladytitania46
@oceanerazzurro
@janettekirchner
@nicolecata
@johnyard2
@mayoisspicyy
@jojofromjerz

Top Tweeters in G10:
@magapanthus
@natalie91231732
@thebonnydoon
@guse_guse
@msalliance
@jagxjr40
@rolynhome
@alfredgliddon
@fionn114
@garrylloydthom2


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