Media Bias on Television and Its Determinants

CitationOreskovic, Petra Laura. 2020. Media Bias on Television and Its Determinants. Bachelor's thesis, Harvard College.

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MediaBiasonTelevisionanditsDeterminants

PetraLauraOreskovic

PresentedtotheDepartmentofAppliedMathematics

Inpartialfulfillmentoftherequirements

ForaBachelorofArtsdegreewithHonors

HarvardUniversity

April2020

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Abstract

Iinvestigatewhatfactorsdeterminethesupplyofnewsstoriesonthethreemajorcablenewschannels—CNN,

FOXNews,andMSNBC.Iuseanoveldatasetofchyrons,thetextatthebottomofthescreen,toexaminewhat

factorscontributetoastoryfromanewswirelikeReutersbeingrelayedoneachofthenetworks.Iidentify

featuresofastory,suchasitsrelevance,politicalvalence,andwhetherthesamestorywasreportedonthe

othertwochannelsassignificant.Thisframeworkallowsmetoinvestigatemediaslant,whichisconceptualized

astheomissionofimportantinformationorstoriesclashingwiththepoliticalviewsoftheaudience(orthe

presumed political views of the channel). I find that media bias does indeedmanifest itself through the

omissionofstoriesthathavepoliticalsignificanceandpartisanvalue.Ialsoinvestigatewhethertheidentified

mediabiasisdemand-driven.IuseaninstrumentforadeclineinFoxNewsviewershiponagivenday—the

existence of a NASCAR race, as the sport primarily attracts Republican viewers— to estimatewhether a

decreaseinFoxNews’dailyviewershippromptsthenetworktoomitstoriesharmfulfortheRepublicanparty

toalesserextent.IfindthatNASCARracessignificantlyreduceFoxNews’viewership,buttheydonotleadtoa

changeinthenetwork’somissivebehavior.

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1. Introduction

Theissueofwhatgetsreportedontelevisionshouldbeimportanttoanyonewithaninterestinthefunctioning

ofademocracy.Inthispaper,Iinvestigatethedeterminantsofthesupplyofnewsontelevision.Thisisnovel,

sincemostresearchfocusesontheeffectsofmediabias,particularlyonvoting,whereasmythesismeasures

thesupplyofTVnewsbeyondjustbiasedcoverage.Manyresearchershaveattemptedtoquantifymediaslant

innewspapers(GrosecloseandMilyo,2005,aswellasGenztkowandShapiro,2010),whileothershavefocused

ontheeffectsofavailabilityandviewershipofchannelssuchasFoxonelectoraloutcomes(DellaVignaand

Kaplan,2004;YurukogluandMartin,2017).Incontrast,Iquantifybiasontelevisionusinganoveldatasetof

chyrons,thetextatthebottomofthescreenduringaTVbroadcast.Itheninvestigatewhethertheidentified

biasontelevisionisdrivenbyaudiencedemand.

TelevisionnewsisanimportantsourceofinformationforthelargestpercentageofAmericans(comparedto

othersourcessuchasonlinenewsornewspapers)andnumerousstudieshaveshownthatthemediainfluence

theoutcomeofelections.Thismeansthatwhatcontentnetworkssupplytotheir(politicallyengagedandolder)

audiences,andwhatcontenttheyomit,isveryimportant.Itisevenmoresoimportantbecausethereexistvery

fewmajornetworks,allwithdistinctprofilesanddedicatedviewership,sofewmajor-networkviewers(Prat

andKennedy,2019)diversifytheirsourceofinformationbywatchingmultiplenetworks.Thiscouldhavevery

importantconsequences,assomeoftheincreasingpoliticalpolarizationcouldbeattributednotjusttopolitical

beliefsbeingreinforcedontelevision,butmorefundamentally,toabasiclackofsubstantialinformationonthe

actionsofpoliticiansortheimportanteventsthathavepoliticalimportance.

Iuseanewdatasetofchyrons,toidentifywhatstoriesfromthenewswireReutersgetreportedonFoxNews,

MSNBC,andCNN.Imeasurebiasbyidentifyingstoriesthatareomittedinspiteof,forexample,beingrelevant

ingeneral,havingpoliticalimportance,beingfavorableforoneofthepoliticalparties,andbeingreportedon

theothercablenewschannels. If suchastory isnot reportedon theremainingchannel, I consider thisan

indicationofbiasedreporting.Ithenconstructanindexthatmeasuresomissionofimportantstoriesbyeach

ofthechannels,andinvestigatewhetherFoxNewsrespondstochangesinviewership.Iutilizeaninstrument

thatreliesontheexistenceofaNASCARracetoexaminewhetherdropsinFoxNewsratings,broughtaboutby

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(male)RepublicanswatchingcarracesinsteadofFoxNews,producechangesintherateofomissionofstories

harmfulfortheRepublicanparty.

Ifindthattherearesignificantdifferencesinwhichnewsstoriesmakeittotheaudienceofeachchannel.This

isparticularly trueofpolitical news,whereFoxNews reportson storiesharmful for theRepublicanparty

substantiallyless.Iidentifyasimilar,butlessextremeeffectfortheothernetworksandtheDemocraticparty,

butIalsofindindicationsofthenewschannelsdifferentiatingtheircoverageonnon-politicalissues.

Therestofthepaperisorganizedasfollows.Section2containstheliteraturereview.Section3explainsthe

conceptual framework for the paper and puts forth predictions. Section 4 discussesmy data sources, the

constructionofimportantindicesusedinthedataanalysis,aswellasthematchingbetweendifferentdatasets.

Section5presentstheempiricalidentificationstrategy.ThefirstpartofSection6presentsresultspertaining

tomeasurementofmediabias,whilethesecondpartdiscussesfindingsonwhetherthemediabiasisdemand-

driven.Section7concludes.

2. LiteratureReview

While the supply of news (on television and in general) and its determinants are little studied, many

researchers have investigated the effects of biased or inadequate supply. Strömberg and Snyder (2008)

estimatetheimpactofpresscoverageoncitizenknowledge,politicians’actions,andpolicyandfindthatvoters

livinginareaswhere,forexogenousreasons,thepresscoverstheirU.S.Houserepresentativelessarelesslikely

torecall theirrepresentative’snameandlessabletodescribeandratehimorher.Atthesametime,those

representativesarelesslikelytostandwitnessbeforecongressionalhearings,serveonconstituency-oriented

committeesandtovoteagainstthepartyline.Durante,Pinotti,andTesei(2019)findthatindividualswithearly

accesstoMediaset,SilvioBerlusconi’sprivateTVnetworkinthe1980’s,weremorelikelytovoteforhimmore

thanadecade later,whenhe first ran foroffice.Theauthorsattribute theassociation toentertainmentTV

producinglesscognitivelysophisticatedandcivic-mindedadults.However,thecontributionofmythesisisthat

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itexaminesthedeterminants,ratherthantheeffectsofparticularkindsofsupply,makingthesupplyofnews

themainoutcomethatisinvestigated.

Ontheotherhand,theredoesexistanimportantbodyofworkinvestigatingmediabias.Themostimportant

paperonmeasuringmediaslantisGentzkowandShapiro(2010).Theyinvestigatethedeterminantsofmedia

slantbyconstructinganindexofmediaslantthatmeasuresthesimilarityofanewsoutlet’slanguagetothatof

acongressionalRepublicanorDemocrat.Theauthorsfindthatreadershaveasignificantpreferenceforlike-

minded news, and that firms consistently respond to consumer preferences. They use religiosity as an

instrument for the political leanings of consumers in a particular geographic area and find that consumer

preferences account for roughly20percentof the variation inmeasured slant in the sample.Thepolitical

leaningsofanewspaper’sownerarefoundtoexplainfarlessofthevariationinslant.Thecrucialdistinction

betweenGentzkowandShapiro(2010)paperandthispaper,however,isinthattheformerinvestigatesslant

innewspapers,andassuch,focusesontheparticularattitudeanewsoutlethastowardsastory,ascaptured

by the phrases it uses to describe certain phenomena, e.g. death tax instead of estate tax. In contrast, I

conceptualizeomissionontelevisionasoccurringtoasignificantextent throughtheomissionofpolitically

unfavorablestories. Ialso investigatewhatdrivesthe identifiedmediaslant,usinganovel instrument.The

instrumentistheexistenceofaNascarraceonaparticularday,whichassumesthatsomeFoxNewsconsumers

will switchaway fromwatching theirnewsandwatch theraces instead. It is inspiredbyZhuravskayaand

Durante(2016),whoinvestigatewhetherIsraelimilitaryattacksaremorelikelytohappenondayswhenthere

arepredictableimportantevents,whichcrowdoutnewscoverageoftheIsraeli-Palestinianconflictandallow

the attacks to attract less attention. I rely on a similar conceptualization of “newspressure,” but I rely on

competitionfromoutsidethenewsarenatodrawtheaudience’sattentionawayfromFoxNews,potentially

changingthenetwork’sbehaviorintheprocess.

MullainathanandShleifer(2005)introduceomissionasapotentialsourceofmediabias.Theypresentamodel

thatposits thatmediaoutlets can choose apolitical slantby selectivelyomitting specific bits of news in a

processtermedslanting,followingHayakawa(1940).Theauthorsgiveexamplesoftwonewsstoriesonthe

same issue that imply radically different conclusions from the same basic piece of information, by citing

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different sources and, crucially for the purposes of this thesis, by focusing on only a certain aspect of the

available information that is eventually reported. Their framework is essential to the conceptualization of

mediabias inthispaper,sinceomissionispositedastheprimarymechanismthroughwhichpoliticalslant

manifests itself on TV. The authors also propose that in a duopoly, the twomedia outletswillmaximally

differentiateonthedimensionofpoliticalslant,ratherthancompetitioneliminatingslant,apredictionthatmy

thesistacklesaswell.

Finally,bothDellaVignaandKaplan(2004)andYurukogluandMartin(2017)studytheeffectsofmediabias.

DellaVignaandKaplan(2004)exploitrandomvariationintheintroductionofFoxNewstocertaintowns,while

YurukogluandMartin(2017)useexogenousvariationincablechannelpositionsforasimilarpurpose.Both

findthatincreasedexposuretoFoxNewsincreasestheRepublicanvoteshare.Mypapercontributestothis

strandofliteraturebyexaminingthemechanismthroughwhichthispersuasioneffectarises,inparticularhow

biasmanifestsitselfontelevision.

3. ConceptualFrameworkandMeasurement

Themost importantprocessthatthispaperaimsto investigate isthetakeupofnewsstoriesonparticular

televisionnewschannelsfromnewswires,andwhatfeaturesofindividualstoriesseemtodetermineit.The

newsstoriesthatappearonnewswiressuchasReutersareassumedtobeunbiasedandimportant,asthenews

channels across the political spectrum are all subscribed to them. This suggests that the news wires are

incentivizedtoreportonthefullsetofnewsstoriesthatappearonagivenday.IpositthattheTVnetworks

thenselectthestoriesthataremostconsistentwiththeirownslant(andalsotheslantoftheiraudience),but

alsoonesthataremostimportant.Heretheimportanceofastoryisconceptualizedastheuniversalrelevance

ofaparticularstoryandisindependentfromthepoliticalslantofachannelanditsaudience.Thismeansthat

regardlessoftheattitudeonemighthavetowardstheactorsinit(andthepoliticalpartytheyareassociated

with),thestoryhasrelevanceforthemasU.S.residents.

Iconsidermediaslantprimarilytoarisefromomissionofimportantinformationorcompletelackofstories

clashingwith thepolitical viewsof the audience, following the framework fromShleifer andMullainathan

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(2005). The reason there is indeed a selection process and the reason it is likely particularly salient on

televisionisthattelevisionisauniquelyconstrainedmedium.Thecontentthatcanbecoveredislimitedby

bothtotalairtimeandthefactthatonlyonestoryatatimecanbecoveredonasinglenetwork,soitisfarmore

likely that certain storieswill in fact be omitted. Furthermore, I expect the already substantial amount of

omissionofparticularstoriestobeexacerbatedduetothenatureofthemarketforTVnetworks.Extremely

highfixedcostspresentbarrierstoentryandensurethatthereareonlyafewmajornationalTVnewschannels,

and their ideologiesareverydistinctanddistant fromeachother.Themost importantconsequenceof the

processofselectionisthatnewschannelslikelyboth(i)omitstoriesthatareinconsistentwiththeirslantand

(ii)exaggerate(orspin)storiesthatareconsistentwiththeirslant.Thelackofcompetitionisalsoimportant

becauseitisdifferentfromthesettingthatShapiroandGentzkow(2010)investigate—oneinwhichthereis

alotofcompetitioninnewspapersprovisionandwithmuchlowerbarrierstoentry.Thisraisesthequestion

whether the bias is driven by the supply or the demand side. Anecdotal evidence, such by Jane Mayer

investigatingfortheNewYorker,chroniclesextensivetiesbetweenTrumpadministrationofficialsandFox

Newsemployees,suggeststhereisthepossibilityofcaptureofthenewsbytheRepublicanparty.Whilethis

supplysidetheoryisverydifficulttoinvestigate,itispossibletoexaminewhetherdemand-sideshockslead

FoxNewstochangeitsbehavior.Ifdemand-sideshocksdochangethecontentFoxNewsproduces,thenthat

reducestheimportanceofthetheoryofpotentialmediacapture.Itisofcoursepossibleforbothdemand-and

supply-sideeffectstoco-exist,butidentifyingdemand-sideeffectswouldsuggestaceilingontheimportance

oftheRepublicanparty’sinfluence(ortheimpactofRupertMurdoch’spersonalconvictions).

However,thereareveryimportantfactorsbeyondachannel’sslantdeterminingthesupplyofstories,suchas

therelevanceofaparticularstory.Ifastoryissimplynotimportant,anetworkmightbecompletelyjustified

inchoosingtoomitit.However,ifdifferentnetworkschoosetosystematicallyomitcertaintypesofstories,that

mightbeanindicatoroftheomissionbeingpoliticallymotivatedandaconsequenceofanetwork’sslant.

Anotherimportantinformativefactorthatmightcontributetounderstandingthesupplyofnewsontelevision

is whether politicians comment on stories that have (partisan) political importance more often. The

assumptionisthatonTwitter(whichwillbeusedtomeasurethepoliticians’attentionandattitudetoparticular

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stories), the main mechanism through which political beliefs manifest themselves is still omission. If a

particularnewsstorydoesnotalignwithone’sworldviewandpartyaffiliation,thenonewillsimplynottalk

about it. For example, a Republican will likely talk about the migrant family separations that the Trump

administrationconductedalotlessthanaDemocratwill.Thissuggeststhatomissionhasanimportantrolein

theexpressionofpoliticalbeliefsbypoliticians,notjustTVnetworks.Imeasurethismechanismbyincluding

theamountofattentionmembersofCongresspaytothestoryonTwitterasacontrolvariable.Includingboth

thetweetingbehaviorofmembersofCongressandameasureofrelevanceatthesametimewillmitigatethe

concernthatsomestoriesaresimplynotrelevantfortheaudienceofaparticularchannel(theconcernbeing

thatit isnotthatthestoryis inconsistentwiththeirviews,butreallyirrelevant),asthetweetscapturethe

variationduetothepoliticalvalenceofastory.Ialsoincludeatentativemeasureofthe“sentiment”ofeach

tweet,i.e.whetheritisexpressingpositiveornegativecontent,toattempttoverifythisconceptualization.

Withallthesefactorsanddynamicsinmind,Iconsideranumberoffeaturesofeachstorythatmightdetermine

whetheritisrelayedbyaparticularnetwork.Iwillexamineitsrelevance,politicalvalence,whethertheother

twochannelsreportedonit,andwhetherReutersreportedonit.

Finally,Ialsoinvestigatewhethermediabiasisdemanddriven.MyprimaryassumptionisthatFoxNewsis

competingforviewerswithnon-newsnetworks:atypicalFoxNewsconsumermighthaveaninterestinsports,

andonthedayswhenthereareNascarraces,theconsumermightchoosetowatchtheraceinsteadofFoxNews.

A studyby theWashingtonPost andUMassLowell identifiedauto racing (Nascar)a sportwithamajority

Republican audience (Bump, 2020), which supports the assumption that Nascar races present a more

substantialshocktoFoxNewsthantotheothernetworks.

Furthermore,IassumeFoxNewsdoesnotonlycompetewithothernewsnetworks;ifconservativeconsumers

arebiasedandgetdisutilityfromreadingnewsinconsistentwiththeirbeliefs,asinShleiferandMullainathan

(2004),theyareunlikelytowatchMSNBCorCNN,asthosenetworksarecateringto(more)liberalaudiences

andaconservativeconsumerwouldgetdisutility fromwatching them.Fox is thereforemore likely to face

competitionforviewersfromnon-newsnetworks.Idonotformallymodelthemediamarket,butShapiroand

Genztkow(2010)provideabriefmodelthatincorporatesbothcirculationandadvertisingrevenueandallows

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fordeviationsfromprofitmaximizationforthefirmdrivenbythefirm’sideology.However,theyinvestigate

whethermediabiasisdemand-drivenusinganinstrumentthatisnotdissimilartotheoneIuse.

ThefundamentalpredictionItest isthatFoxNewschangesitsreportingbyomittingfewerstoriesthatare

harmfulforRepublicansifthereisalargedropinviewership.FoxNewsmightdosobecauseareductioninits

viewershipmakesitmorelikelythattheywillseekoutaudiencesdifferentfromtheircoreviewers,whoare

definedessentiallybybeingpoliticallyconservative.Thisassumesthatthereexists(some)heterogeneityinthe

beliefsofFoxNews’audience.Inorderforthispredictiontobeplausible,itisthemoreconservativeviewers

whoshouldswitchfromwatchingFoxNewstoNascar.SinceitismostlymenwhowatchNascar,andmenare

ingeneralmoreconservativethanwomen(perhapsthegeneralstatisticisnottruewithinthesubsetofFox

Newsviewers,butthisseemslesslikely),itisreasonabletoexpectthattobethecase.IfFoxisfoundtoomit

fewerstoriesthatharmtheRepublicanPartyonthedaysofNascarraces,thenatleastsomeofitspolitically

biasedreportingisdrivenbyaudiencedemandforit.

Ontheotherhand,however,itisalsopossiblethatFoxNewsdoesnotchangeitspoliticalslant,butitstilldoes

changeitsbehaviortoattractmorewomen(butnotnecessarilymoreliberalorpolitically“moderate”women).

Thismightconstitutecoveringmorestoriesthathavenoobviouspoliticalcontent–“softnews”storiessuchas

thoseaboutMeghanMarkle.Althoughthisisachangeincontentbutnotnecessarilypoliticalslant, itisstill

measuredthroughtheconceptofomission,asFoxNewswillneedtoomitfewerstoriesthatexistaboutMeghan

Markleandsimilartopics.ThispossibilityisdiscussedinSection5andalsotestedempirically.IfFoxisfound

tonotchangeitspolitically-motivatedomissivebehavior,butchangesitscontenttoappealtowomenmore,

thenthisstillindicatesthatFox’snewscontentisdemand-driven,evenifnotnecessarilyintermsofpolitical

slant. While that would not directly provide evidence that its political bias is also demand-driven, being

responsive in such away to audiences in one facet of its behaviormightmake itmoreplausible that it is

responsiveinotherways,includinginitsprovisionofpoliticalbias.

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4. Data

I. Variables

Iuseadatasetcontainingchyrons,thetextatthebottomofthescreenduringabroadcastfromArchive.org.

Thedatasetincludesmorethan600,000chyronsthatappearedonthethreemajorcablenewsnetworks(Fox

News,CNN,andMSNBC)intheperiodbetweenMarch19thandNovember26thof2018.Thisperiodischosen

becausethedataisassembledfrommanydifferentsourcesandspansdifferentperiods,whilethisisthelargest

setofdatesforwhichallthevariablesexist.Thedatasetalsocontainstheexacttimeeachchyronwasaired

duringabroadcastoneachday.IalsouseadatasetfromKaggle.comconsistingofReuters122,987articles

publishedontheReutershomepageduringthesametimeperiod.Thedatasetalsocontainsthedatethearticle

waspublishedandthearticles’title.

IobtainthedatasetcontainingallthetweetIDsbyRepublicanandDemocraticmembersofCongressinthe

periodconsideredfromaHarvardDataversedatasetsharedbyJustinLittman.AsTwitterdoesnotallowfor

tweets themselves tobepublicly shared, thedataset contains scraped tweet IDs that I convert into tweets

themselvesusingaprogramcalledHydrator.AllthetweetsareclassifiedaseitherRepublicanorDemocratic

basedonthepartymembershipofthetweeter.Twitterdataareespeciallyappropriatebecausetheyprovide

high-frequencyinformationthatcapturestheopinionsofeachparty’spoliticiansateverymomentintime;their

reactiontoaparticularstoryisusuallyimmediate,andtheyreactquiteoften.Furthermore,Twitterdatamight

allowmeto,inanimpartialandsystematicway(thatdoesnotrequiremetomakeapersonaljudgementon

each story), classify each story as either favorable or unfavorable for each party. The use of tweets by

CongressmenmirrorsthestrategyusedbyShapiroandGentzkow(2011),whouseCongressionalspeechesto

classifyphrasesaseitherRepublicanorDemocratic.Inthiscase,IusetweetsbymembersofCongressasthey

are immediately labeled—weknowthepartyaffiliationofeach tweeterandcanseehow it relates to the

contentthetweetercommentson.ThetestableassumptionisthatonTwitter,themainmechanismthrough

whichpoliticalbeliefsmanifestthemselvesisstillomission.

InordertoaggregatethisinformationfromTwitteraboutpartisanattitudestowardseachparticularstory,I

createanindexthatmeasureshowfavorableitisforRepublicansandDemocrats.Theindexrangesfrom-1to

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1.Forvaluesbetween-1and0(notincluding0),thereexistmoretweetsfromRepublicans’accountsaboutthe

topicsthantweetsfromDemocrats’accounts.Forvaluesbetween0and1(notincluding0),thereverseistrue.

Theindextakesonavalueof0ifthereisanequalnumberoftweetsbyeachsideoriftherearenotweetsatall.

Thisindexprimarilycapturesthedegreetowhichacertainstoryisanissuemainlyofinteresttoonlyoneparty,

whichisinlinewiththepredictionthatpoliticianswillalsoomiti.e.notcommentonstoriesthatdonotdepict

theirpartyinafavorablelight(orstoriesthatdodepicttheirrivalpartyinafavorableway).

Thisindex,byitself,mightfailtocapturestoriesforwhichthereisanequalamountofresponsefromeachof

the parties, since the above-constructed index does not discriminate between a story with this equally-

numerousreactionscenarioandonetowhichthereisnotwitterresponsefromeitherside.Thisisexpectedto

berareforstoriesthatproducealargenumberoftweets,asitisprobabilisticallyunlikelythatbothparties

produceexactly137tweets,forexample.However,Ialsoincludeanindicatorfortheoverallnumberoftweets

bythepoliticiansaboutagivennewsstoryonagivenday.Itbothcapturestheroleofastoryhavingpolitical

contentindeterminingitscoverageanditcontrolsforthepossibilitythattheremightbeanequalamountof

tweetsbyeachparty,butmoreimportantly,forthepossibilitythatpoliticiansdonotomitstoriesthatdonot

suittheminthesamewayTVnetworksdo.Iexpectthattheystilldoomitthosestoriestoasubstantialextent

(asdescribedearlier),buttheprocessofomissionmightbesomewhatlesspronouncedduetotheabsenceof

theconstraintonthenumberoftweetsonecanpost,andthefactthattheymightdefendthemselvesagainst

accusationsofmisconduct.

Iconsideranumberoffeaturesofthestorythatmightdeterminewhetheritisrelayedbyaparticularnetwork.

Iexamineitsrelevance,politicalvalence,andwhethertheothertwochannelsreportedonit.Imeasurethe

relevanceofeachstoryusingdataonwhetherBBCreportedonthestoryinquestionbutexcludingstoriesthat

concerntheUnitedKingdom.AstheBBClikelyonlyreportsonstoriesconcerningtheUnitedStatesthatare

particularlyimportant(asthemajorityoftheirfocusisontheUnitedKingdom),thisprovidesaconservative

measureoftheimportanceofstories.ItexcludessomestoriesthatU.S.viewersmightdeemimportantandstill

relieson theconstrainedmediumthat is television, sonotall important storiesarecaptured,but it seems

reasonabletoconcludethatthemeasurewillcapturethemostimportantones.TheBBC’scoveragefiltersthe

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stories by importance, rather randomly sampling them. Furthermore, if onebelieves thatBBChas a slight

liberalbias,theremightbesomeslantedreporting.However,thisshouldbeamuchsmallerconcern,asBBC’s

coveragedoesnotaffectU.S.electoralpolitics,sothatproduceslessofanincentivetoslant,regardlessofthe

attitudesoftheBBC.Ontheotherhand,biasedBritishconsumersshouldcareonlyiftheyareideologueswhose

politicalbeliefscanbetranslatedtoothercountries’politicsinameaningfulway.Forexample,someonewho

supportsBrexitintheUKwouldnotnecessarilysupporttheRepublicansintheU.S.Therefore,thedemandfor

biasedreportingabouttheU.S.shouldnotarisefromtheconsumers’concernsfortheirownwell-beingorthat

of their community, unless the story concerns international relations. However, even in those cases, one

expectsthatthereshouldgenerallynotbedifferencesacrossthepoliticalspectrumastowhatisanimportant

outcomeforBritain’srelationshipwiththeUnitedStates.Onecanseethatinthecaseofnegotiatingatrade

deal,forexample—itislikelygoodnewsregardlessofwhethertheBritishconsumerisliberalorconservative.

Thus,international(andU.S.)storiesthatarerelayedtoBritishconsumersarelikelystillthemostimportant

ones.

ThepoliticalvalenceismeasuredaswhethermembersofCongressandSenatecommentedonthestoryatall

onTwitter(regardlessoftheirpoliticalaffiliation).Veryimportantly,Ialsoexaminewhethertheothertwo

channels reported on the story, which will presumably capture the political slant of the network whose

coverageisbeingestimated.

Finally,Iuseadatasetcontainingthenumberofdailyviewersforeachofthecablenewsnetworks(FoxNews,

CNN, andMSNBC,butnotBBC)betweenMarch19th andNovember26thof 2018. I obtain thedataset by

scrapingtheinformationfromAdweek’sTVNewserwebsite.However,thedataqualityforMSNBC’sviewership

islower—therearemanymissingvalues,sothatdatasetisnotutilizedextensively.Ialsouseadatasetfrom

CBSSportsthatcontainsinformationonthescheduleofNascarracesinthetimeperiod.TheNascarseasonin

2018startedonFebruary18thandendedonNovember18th,meaningthatitalmostperfectlyoverlapswiththe

periodtheotherdatacover.This,aswellastherelativelylongdurationoftheraces(upto4.5hours,whichis

expectedtogenerateasubstantialreduction inthenewsnetwork’sviewershiponthatday) is thereasonI

chooseNascarraces.

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II. TopicsInvestigatedandMatchingMechanism

IuseasetofstoriesselectedfromFoxNews’,CNN’sandMSNBC’slistsofthemostimportantstoriesoftheyear.

IaggregatestoriesbydayandsearchboththeReutersarticlesandchyronsusinganumberofkeywords.Ithen

countthenumberofchyronsreferringtothetopiconthatday.Table1includesthelistoftopicsinvestigated

andthekeywordsusedtoidentifythem.Ichoosethetopicssothatthemajorityoftopicsharmfulforeachparty

involvesscandals,andpreferablylegalactiontakenagainstpersonsaffiliatedwiththatparty.Thisiseasierto

achievewithstoriesharmfulforRepublicans,astheyarethepartyinpowerduringtheperiodthatisexamined.

Whileinsomecasestheclassificationismyownvaluejudgment,itishardlycontroversial,forinstance,that

ElizabethWarren’sclaimtobeNativeAmericanwasharmfulforherasaDemocraticSenator.

Theunderlyingassumptionofthismatchingstrategyisthatdailyfluctuationsintopicsthatarereportedon

televisionreflectdifferentnewsstories.Forexample,iftwochyronscontainthekeywordIranbutoneappears

onMonday,andtheotheronThursday,theyarelikelyreferringtodifferentstoriesbecauseofthe24-hour

newscycle,wherenostorylastsformorethandayunlessthereare,stillaspartofthesamestory,immediate

and importantdevelopments.Thismeansthatstories fromReuterscanbematchedwithchyrons from, for

example,CNN,iftheybothcontainoneofthegivenkeywords,suchasParklandandFloridashooting,onasingle

day.CNN,MSNBC,andFOXareaprioriconsideredtohaveacertainpoliticianslant:MSNBCisthemostliberal

network,CNNiscenter-left,andFOXisconservative.ThisclassificationfollowsGrosecloseandMilyo(2005),

butitisalsoratherpopularlyaccepted.

Ialsocreatepartitionsofthedata.OnesetthatIuseforregressionscontainsstoriesharmfulforRepublicans,

and it is constructed by adding together (concatenating, notmerging) the individualmatcheddatasets for

storiesaboutMichaelCohen,BrettKavanaughetc.AdatasetofstoriesharmfulforDemocratsisconstructedin

thesameway,aswellasadatasetwithneutralstories.

Chyronsareanappropriatetooltostudythecontentoftelevisionbroadcastsbecausetheycondensethespoken

information,presentingtheviewerwiththeessentialinformationrelatedtoanevent.Thismeansthatonly

storiesthatareindeedaboutillegalimmigrationwillbecodedassuch,insteadofinstanceswhereaTVguest

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mightmentionitinpassing,assuchcoveragelikelydoesnotleavetheviewerswithanysenseoftheimportance

ofagivenissue,andlikelyshouldnotcountasstoriesaboutimmigration.However,evenmoreimportantly,

chyronscanreflecttheattitudesandintentionsoftheparticularTVnetworkbecausetheyaregenerallycreated

by the chief editor of each show on a network. This matters because TV networks often claim their

programmingisimpartial,arguingthattheyfeatureamultitudeofperspectivesfromfiguresacrossthepolitical

spectrum(theformermottoofFoxNewsisinfact“FairandBalanced”),andlettheirviewersdecidewhatthe

truth inadebate is.While this claimhasattractedcriticism (ColumbiaReviewof Journalism,n.d), aspoor

journalisticpractice, thecontentof thechyronsrepresentsdirecteditorial input, i.e.what thenetworkhas

decided that the takeaway fromadiscussion shouldbe,or at thevery least,whichof theguestsholds the

opinionmostworth highlighting. This is evident as chyrons are evenmore limited in the amount of their

contentthanaretelevisionbroadcastscomparedtonewspapers.

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5. EmpiricalStrategy

To identifywhether stories related to a particular topic are on average reported on Fox News I estimate

whereFOX,CNN,andMSNBCdenoteeitherthenumberortheshareofchyronseachnetworkcontributedto

thecoverageofthestoryonthatday.Eachnetwork’spercentage-wisecontributiontothetotalcoverageofan

issue on a given day, rather than the raw figure, is chosen in all but one regression. This is to isolate the

relationshipbetweenthenetworks,ratherthanfocusontheactualnumberofstories.Thisistherelationship

that is much more at interest than the sheer number of stories about Stormy Daniels, for example. The

”relevance”variable is thenumberofchyronsBBCdevotes to thatparticular topic (excludingchyrons that

specifically refer to theUnitedKingdom)on a givenday.Thevariable ”congress_ratio” corresponds to the

congressionalratiodescribedabove,whereas”total_tweets”correspondstothetotalcountofcommentsby

membersofcongressonthatparticulartopic.Bycontrollingforthecongressionaltweets(thepoliticalvalence

ofit)regardingthestory,Icandisentanglethepartisanvalueofthestoryfromitsgeneralimportance.This

mitigatestheconcernthatonemight(rathercynically)arguethatstoriesaboutborderseparationsdonothave

bearingonindividualswhoopposeimmigrationandassuchtheydonotmeritalotofattentionfromthemedia.

Anyof theother two (American)networkscouldhavebeenchosenas thedependentvariable instead,but

because both of the other networks are liberal, the coefficients onMSNBC and CNN are both expected to

demonstratethedifferencebetweenliberalandconservativecoverageofanissue.Thisiswhytheyarekept

togetherasindependentvariables.

Measuring political valence through tweets is expected to capture another kind of omission effect, where

CongressionalRepublicansorDemocratsonlytweetaboutstoriesgoodfortheirpartyortheirownplans,orit

mightcapturetheirattitude.Ifthecoefficientonthisvariableturnsouttobenegative,thenthatmightsuggest

thatpoliticiansdonotfailtocommentonstoriesthatarebadfortheirparty,insteadchoosingtofireback.

Introducingsentimentanalysisandcodingeachofthetweetsaseitherpositiveornegativemightprovidemore

insightintothis.

16

Finally,Iuseaninstrumentalvariableapproachtoexamineifthe(expected)mediabiasisdemand-driven.I

investigatewhetherchangesincontentFoxNewsemitsaredrivenbychangesintheirviewership.However,

as viewership is endogenous, oneway to disentangle its effect is to use an instrumental variable, namely

whetherthereexistedaNascarraceonagivenday.Asidefromthefactthattheyaremuchmorepopularamong

Republicans,Nascarracesareaveryappropriateasaninstrumentforanumberofotherreasons.Theylasta

longtime(upto4hours,sotheyareasizableshocktoFox’sviewership)andthereareonly33ofthem,sothey

arenotveryfrequent(theyareplausibleasashockthatisnotplannedfor,unlikebaseballgames,whichhappen

everyday).Crucially,theirschedulingisalsoassumedtobeindependentofchangesinFoxNewsviewership.

Thisisplausibleasthescheduleoftheracesisdecidedmonthsinadvance,beforeFoxNewsfluctuationsare

apparent.Theymightbescheduledtoattractmoreaudiences,sotheyaremorelikelytohappenonaweekend.

I therefore include whether a race happened on a weekend as a control. Consumer behavior during the

weekendmightsignificantlydifferfrombehaviorduringtheweek,androughlyathirdoftheraceshappenon

a weekend. However, if this Nascar organizers exhibit this behavior, then they are perhaps only seeking

weekendswherethereislittlecompetitivepressureintermsofotherprogramming,whichmakesiteasierto

ascribeapotentialreductioninFoxNewsviewershiptotheracesthemselves.

Theprimaryissuewiththisstrategyisthatitispossiblethatasingle-dayNascarraceisnotalargeenough

shockforFoxNewstoberesponsiveto.Perhapssmallshocksarenot“worthit”forFoxNewstochangeits

reportingstrategy.Ontheotherhand,ifitisresponsivetoaudiencedemand,itmightchangeitscoverageto

attractmorefemaleconsumers,as it is likelymostlymaleonesthatswitchtoNascar.However,thiscanbe

examinedempirically,byfocusingonthe“softnews”storiesinthesample.NewsstoriesconcerningMeghan

MarkleorthedeathofKateSpadearemorelikelytoappealtowomen,soIcanidentifywhetherFoxNewsdoes

changeitsbehaviortoincludemoresuchstoriesusingthesameinstrument.Onemightalsoraisetheissuethat

perhapssportsfansformamuchlargerpercentageofCNN’s(orMSNBC’s)viewership,butwhethertheraces

produceadisproportionateshocktoFoxcomparedtotheotherchannelsisempiricallytestable.Consequently,

ifnosuchshifttoward“soft”newsisdetectedandthedeclineinviewershiponlypertainstoFoxNewsandnot

theothernetworks,themainconcernthatpersistsisonlythattheNascar-inducedshockisnotsizableenough

toincentivizeFoxtochange.However,ifFoxdoesnotchangeitsbehaviortoappealtowomeneither(whichis

17

possibly a less costly strategy), then this makes the idea of its responsiveness to audience demands less

persuasive.

6. ResultsandDiscussion

I. Media Bias

Ifirstaggregatethecoverageofalltopicsbyconcatenatingthedatasetsforeachoftheaforementionedtopics

andconsideringtheaverageeffectofeachofthefeaturesofstories(suchasrelevanceorthecongressional

twitterratio)acrossalltopics.Table2presentstheresultsforallofthetopicslistedinsection5(exceptthe

neutralstories),meaningthatincludes7topicsfavorableforRepublicans,7topicsfavorableforDemocrats,

and4topicsthatmightbefavorableforeitherparty,dependingontheparticularstory.Allofthestoriesinthe

first twosets consideredarearguably important, suchasMichaelCohen,Trump’s former lawyer,pleading

guiltytoanumberofaccusations.

Ifirstfocusonspecifications1-4,whichmeasureeachnetwork’srawnumberofchyronsdevotedtoaparticular

topiconagivenday.Inspecifications1-4,thereseemstobeastatisticallysignificanteffectassociatedwithall

ofthevariables.Asexpected,increasingthecongressionalratio,i.e.thereexistingmoretweetsbyDemocrats

abouttheparticulartopiconagivenday,makesitmuchlesslikelythatFoxwillreportonthestoryonagiven

day.Theestimate,whichissignificantatthe95%level,suggeststhatifonlyDemocratstweetaboutagiven

topiconagivenday,thereisanaverage0.425reductioninthenumberofchyronscoveringtheissueonFox

News.Interestingly,thegeneralattentionmembersofCongresspaytothetopicontwitter(“TotalCongress”)

hasarelativelysmalleffect—itispositivelyassociatedwiththenumberofFoxNewschyrons(asexpected),

buttheeffectismuchsmallercomparedtotheBBC’scoverage.“Totalcongress”producesasmallereffectthan

thecongressionalratio,suggestingthatpartisanshipisperhapsmoreimportantthanthegeneralimportance

ofastoryindeterminingwhetherFoxNewscoversit.However,theBBC’scoverageisanimperfectmeasure

asitsfocusisnotonnewsconcerningtheUnitedStatesinparticular,sowithabettermeasureofimportance

thescaleoftheeffectmightbereduced

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Additionally,ifthereexistsaReutersstoryaboutagivenissueonaparticularday,onaveragethereisa1.186

increaseinthenumberofchyronsregardingtheissueonFoxNews.ThissuggeststhatReutersarticlesare

associatedwithalargepositiveincreaseinthenumberofchyronsreportedonbyFoxNews.

WhilemorecoveragebytheCNNorMSNBCreportingonissueispositivelyassociatedwithmoreFoxNews

reportingonthestory,thecoefficientsonthevariablesforMSNBCandCNNareverysmall.Thecoefficientsin

allfourspecificationssuggestthat,onaverage,aone-chyronincreaseinMNSBC’sorCNN’scoverageofanissue

onagivenday isonlyassociatedwithan increaseofbetween0.1and0.2chyronsonFoxNews.Thisdoes

suggestthatFoxreportsontheissuesCNNorMNSBCreportontoamuchlesserextent,althoughtheidentified

effectisnotexplicitlynegative.ThevisualevidencemightbeanindicationthatthespecificationsusedinTable

1mightnotbesensitiveenoughtocapturetheeffectofomissionfully—CNNstillis(positively)predictiveof

Foxreporting,astheydocorrelate.Thisisevidentas,moreoftenthannot,Foxwillstillreportonastoryonthe

samedaywhenCNNdoes,butCNNmightdoitonmanyotherdayswhenFoxdoesnot—thesetofCNNstories

willbelargerforstoriesthatareunfavorableforRepublicans.

19

However, anotherway to investigate this relationship is touseFoxNews’percentage-wise contribution to

overallcoverageofastoryastheoutcome.Inthatcase,thevariablesthatpreviouslymeasuredthenumberof

CNN’sorMSNBC’schyronsnowmeasurethepercentagetheycontributetothedailycoverageofthetopicat

handaswell. This isdone in column(5)ofTable2. In this specification, I find thatCNN is stillpositively

predictiveofFoxNewsreportingonparticularstory(althoughitseffectismuchsmallerthantheoneReuters

produces, for example). Very importantly, MSNBC’s percentage increasing is associated with Fox News’

percentagedecreasing,indicatingthatthetwonetworksactinoppositedirections.IfMSNBCreportsonastory,

FoxNewlikelyreportsonitless,andviceversa.

Figure1:NewsCoverageofStormyDaniels

Furthermore, Figures1 and2depicts thenews coverageof storiesharmful toDonaldTrumpandprovide

furtherevidencefortheomissionofpartisannewsstories,especiallyonFoxNews.Itisapparentthatstories

thatareharmfulfortheRepublicanparty,suchastherelationshipbetweenpresidentTrumpandhislawyer

Michael Cohen, aswell aswith the porn actress StormyDaniels, are consistently omitted from FoxNews’

coverage.We can see that FoxNewsdoesnot generally report on the issue onmost dayswhen the other

networks do (and when Reuters does, but that is not very clearly visible on the graph due to its scale).

Furthermore,onthedayswhenFoxNewsdoesreportonthosestories,itprovidesamuchlowervolumeof

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storiesabouttheissue.Forexample,attheverypeakofcoverageofMichaelCohen,thereisanextremelyhigh

numberofmorethan400chyronsperdaydevotedtothestoryonCNN.Incontrast,Foxdevotesamere50

chyronstothestorythatday.

Figure2:NewsCoverageofMichaelCohen

Figure3:NewsCoverageofIllegalImmigration

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Ontheotherhand,newscoverageofillegalimmigration,aswellasthe“caravan”ofimmigrantsheadingtothe

U.S.fromCentralAmericareceivedmuchmoreattentionfromFoxNews,relativetoCNNandMSNBC.Onemight

arguethatitisoutsizedandrepresentsspin,butthatisperhapsavaluejudgmentIwillrefrainfromhere.

Tofurtherexaminethebehaviorofeachofthenetworks,Ianalyzethetopicsbydividingthemintothreesets.

OnecontainsstoriesthataredamagingfortheRepublicanparty,anotherexaminesstoriesdamagingforthe

Democraticparty,andfinally,anotheroneexaminesstoriesthatdonothavepartisanvalue(ortheirvalueis

notclear,buttheyareveryimportant).Inallfurtherregressions,Iusethecablenewsvariablesexpressedas

percentagesoftotalcoverageofatopiconagivenday.Thisspecificationseemstoexpresstherelationship

betweenthosevariablesbetter(especiallywhenFigures1-3areexamined),whiletheylargelydonotaffect

coefficientsonothervariables.

Tables3and4mostlyconfirmtheintuitionfromTable2,althoughthecoefficientsarenotalwayssignificant.

Thismightalsobeinpartduetothefactthattheregressionsareunderpowered:thesedatasetsaresmaller

thantheentiredatasetthatcontainsallthedays14timesover—onceforeachofthetopics.Thecoefficients

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do,however,mostlyretaintheirexpectedsigns.Crucially,increasingMSNBC’spercentageisassociatedwith

lesscoveragefromFoxNews,whereasifCNN’spercentageincreases,Fox’spercentagedoesaswell.Itsuggests

thatMSNBC’scoverageis“contrary”toFoxNews’.

The focus of this analysis is to disentangle the differences between the networks, so the effect of Reuters

covering the topic, aswell as theBBC, isnot crucial. It also lesseasily lends itself to interpretation, as the

outcomehereisthepercentageofFox’scoverage,butitisencouragingthatbothvariablesmostlyretaintheir

positivesignacrossdifferentspecifications.

IncreasingthecongressionalratioisassociatedwithFoxcontributingalowerpercentagetothetotalnumber

ofstoriesforbothstoriesthatareharmfulforDemocratsandharmfulforRepublicans.Theeffectislargerand

statisticallysignificantonlyforstoriesharmfulforDemocrats,whichiscurious,butthisisnottooconcerning

duetotheaforementionedpowerissue,andpossiblyduetothefactthatallofthevariablesarelikelyhighly

correlated.Thecongressionalratioandthetotalnumberoftweetsoriginatefromthesameinformation,and

thecongressional ratiosarealsoexpected tobehighlycorrelatedwith thenetwork’sbehavior,as theyare

effectivelymeasuringthesamebehaviorintwodifferentways.

23

Furthermore,ifindividualregressionsareexamined,wheretheonlyindependentvariableisthecongressional

ratio,wecanseethatcongressionalratiosarehighlypredictiveofthe“networkratios.”Thenetworkratiois

definedverysimilarlytothecongressionalratio,whereittakesonavalueof1storiesonaparticularissueon

agivendayareonlyfeaturedonMSNBC(andnoneonFox)andavalueof-1ifallofthosestoriesappearonFox

news(andnoneonMSNBC).Themorestories(outofthetotal)appearonMSNBC,themorepositivetheratio,

whereasifmoreappearonFox,itisnegative.Thismeansthatacongressionalratioof0.25doesnotmeanthat

25% of the stories were on Fox and 75% on MSNBC, but instead that 62.5% were on MSNBC (equal to

100*1.25/2),and37.5%onFox.Thisdefinitionwaschosentoaidvisualizationsbelow.Furthermore,theratio

isnotsensitivetousingCNNasthe“liberal”channel—theresultsareverysimilarifitisusedinstead,but

MSNBCischoseninsteadbecausehavingtwochannels(aswellastwoparties)easesinterpretation,aswellas

theconstructionoftheindex.Ifthereisanequalnumberofstories,oriftherearenone,theratiotakesona

valueof0.Furthermore,itisworthnotingthattheexpectedsignonthecoefficientforthecongressionalratio

ispositiveintheregressionwherethenetworkratioistheoutcome.Thisisbecausetheratioishigher(and

positive)whenthereismoreliberalcoverageofanissue,whereaspreviously,ifFoxNewspercentagewasthe

outcome,thenmoredemocratsdiscussinganissuewasthoughttobeassociatedwithlessFoxNewscoverage.

Table5indicatesthatthecoefficientforthecongressionalratioisverypredictiveofthenetworkratiobothfor

storiesharmfulforDemocratsandstoriesharmfulforRepublicans.ForstoriesharmfulforRepublicans,the

coefficientisstatisticallysignificantandsizable,asa1-pointincreaseinthecongressionalratioisassociated

witha0.115pointincreaseinthenetworkratio.ThecongressionalratioforstoriesbadforDemocratsproduces

astatisticallysignificant0.175increaseinthenetworkratio.

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Anotherwaytotestthesefindingsistoexaminethedistributionsofthecongressionalandthenetworkratios.

Ifmembersofcongressdoindeeddiscussstoriesharmfulfortheirpartytoalesserextentandstoriesharmful

forthecompetingpartiesalot,thenwemightbeabletoidentifythisvisually.

Figure4:DistributionofNetworkandCongressionalRatiosforAllStoriesHarmfulforRepublicans

Figures4and5seemtoconfirmthisintuition.Thedistributionofcongressionalandnetworkratiosconcerning

stories thatareharmful forRepublicanshasanextremelyprominentnegativeskew(ignoring the0-valued

entries).Thecongressionalratiosareinfactevenmoreextremethanthenetworkratios,whichisencouraging,

asitsuggeststhatCongressionalRepublicanstrulyarenotcommentingonstoriesthatmighthurttheirparty,

whereas Congressional Democrats are placing a lot of emphasis on those same stories (harmful for

Republicans).Thisvalidatestheassumptionthatthereisanomissionprocessatplayincongressionaltweets

aswell.Furthermore,itseemsthattherearefewerinstancesofthenetworkratiobeingentirelydominatedby

MSNBC. This might either suggest that network coverage is at least a bit less biased than the politicians

themselves,butthismightalsobethecaseiftherearelotsofdayswhenthereareveryfewtweetsoverallbut

all of them are byDemocrats,whereas not allminor newsmight provoke coverage from any of the news

stations.Thatwouldproducemany1-valuedcongressionalratios,butnotasmanynetworkratiosvaluedat

25

exactly1.Thisseemsmoreplausiblegiventhatthenetworkratioexceedsthecongressionalratioatallother

valuestotherightof0.

Figure5:DistributionofNetworkandCongressionalRatiosforAllStoriesHarmfulforDemocrats

Ontheotherhand,forstoriesthatareharmfulforDemocrats,theskewislesspronounced,butthedistribution

is still left-skewed, as expected. Republicans comment on stories harmful to Democrats more than those

harmfulforthemselves(whenthequantityiscomparedtotheoneinFigure4),butstillquiteabitlessthan

DemocratsdointheparallelsituationinFigure4.However,Democratslikelytweetmoreabouttopicsnegative

forRepublicansbecauseRepublicansareinpowerintheperiodexamined,andtherearesimplyfewerstories

(andfewerdayswhenthestoriesarerelevant) thatareharmful forDemocrats,so thereare fewerspecific

affairstheycancriticizetheDemocratsfor.Itisquitepossibletheyarenotlesscriticalingeneral,butinstead

thattheycriticizethemforgeneralapproaches,ratherthanspecificeasilyidentifiablescandals,whicharethe

focusofthisstudy.Additionally,RepublicanssimplytweetlessthanDemocrats:theirtweetsconstitute41%

ofthesampleoftweets.Furthermore,ifweinspectspecificcoverageofillegalimmigrationandthe“caravan,”

animagethatisequallydramaticastheoneinFigure4emerges.Thissuggeststhatforstoriesthathavean

extremelyclearpartisanfavorability(arguably,storiesaboutthespaceforcearenotasimportantpoliticallyas

26

thescandalsinvolvingScottPruitt,forexample),thesamedegreeofpartisanshipisevidentinCongress,andin

factitismoreextremeforthenetworkratio,whichhasanextremeleftskew.

Figure 6: Distribution of Network and Congressional Ratios for Stories about the Caravan and IllegalImmigration

Figure7:DistributionofNetworkandCongressionalRatiosforNeutralStories

27

On theotherhand, ifwe inspect stories thathavevery littlepolitical content, suchas thoseaboutMeghan

MarkleorKateSpade’ssuicide,thepolarizationismuchlessapparent.Whilethereisstillclusteringatextreme

values,thefrequencyofextremesislowerthaninallothergraphs,andthedistributionislargelysymmetric.

Inorderto further investigateavoidanceof discussingtopicsthatharmone’sownpartyonTwitter, Ialso

performedsentimentanalysisoneachofthetweetsthatpertainstoaparticulartopic(e.g.StormyDaniels)

usingpython’sTextBlobpackagewhichistrainedonmoviereviewstomeasurethepositivity/negativityofa

text.However,theestimatesarelikelyveryunreliable,asthemeanestimated“sentiment”fortweetsabouta

particularpartisantopicisextremelysimilarforbothDemocratsandRepublicans,sotheyarenotreported

here.Ialsoexaminedthetweetsmanually,andthereseemstoexistapositivebiasintheclassificationoftweets

(aswellassubstantialnoise),butasitwasverydifficulttodeterminewhetherthebiassystematicallydiffered

forthetwoparties,thiswillneedtobeanalyzedusingalternativesentimentanalysisapproachesinthefuture.

It seems that sentiment analysis cannot aidushere, but the congressional andnetwork ratiosdo seem to

confirm the initial hypothesis of omission of harmful stories happening in Congress as well, so it is not

necessary.

28

Ialsoinvestigatehowthenetworkscoverneutralstories,whosedistributionwasexaminedinFigure7.

Thesefindingssuggestthatthenetworksmaybepursuingastrategyofmaximaldifferentiation.Thecoefficient

onMSNBCremainssignificantlynegativeinpredictingFox’spercentageofstories,andCNNisstillsignificantly

positive.WhileFigure7suggeststhereisnotasmuchpolarizationbetweenthenetworks,itispossiblethatthe

networkratiosandthecongressionalratiosthatarepositivedonotcoincide(thesameistrueforthenegative

ones),andtheymatchedbyday.InFigures4-6,thisislessofaconcernbecauseoftheveryextremeskewthe

distributions have (so if a distribution is right skewed, for example, there are fewer possible negative

congressionalratiosthatcouldatallbematchedwithpositivenetworkratios).Furthermore,despitetheless

evidentpolarization,thenetworkratiosdoseemslightlyinverselycorrelatedwiththenetworkratios,which

impliesthatthecongressionalratiosshouldbepositively(refertodiscussiononpage20)correlatedwiththe

FoxNewspercentage,whichiswhatIdofindinTable6.

Wecanbemorecertainthatthechangeinthesignforthecoefficientoncongressionalratiosthatweobserve

inTable6shouldnotchangeourconjecturesaboutthemreflectingpoliticalbiasifweexpandthedatasetfrom

Table 6 to includemore politically valent stories. In this case,we examine stories concerningKate Spade,

MeghanMarkle,AnthonyBourdain,butalsostoriesaboutNorthKorea,Iran,andJamalKhashoggi’smurder.

Thelattersetofstoriesareimportantpolitically,buttheydonotexplicitlyfavoronepartyoranother.Thebias

anetworkmightexhibitinrelationtothoseissueswilllikelybereflectedintheirattitudetotheparticularnews

stories(aboutIran,forexample),ratherthanincompletelyomittingthem.

Table 7 confirms this intuition. The size of the coefficient on the congressional ratio largely dramatically

declines,whiletheothercoefficientsremainsimilartotheonesinTable6.Interestingly,whileReutersdidnot

predict neutral stories being relayed by Fox in Table 6, the coefficient is much larger and significant in

predictingcoverageofthelargersetofstoriesthatincludespoliticallyimportantstories.Itseemslikelythat

networksdifferentiatetheircontentnotonlyalongpoliticallinesbutseektoshowdifferentcontentingeneral.

However,theevidencefromTables2-5,aswellasFigures1-6suggeststhatthereisasubstantialamountof

omissionofstoriesthatareharmfulforthepartythatalignswithanetwork’spoliticalviews.

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II. Demand-DrivenBias

After identifying omissive behavior by the networks and its predictors, I proceed to define omission. I

determinewhetherthereexistedan“importantstory”onaparticularissuebycreatinganindicatorvariable

thatmeasureswhether Reuters and at least two of the cable news networks (I includeBBC in this list of

networks) reported on the story. (I also create amore conservativemeasure, that only relies on Reuters

reportingonit).IthendefineanotherindicatorvariablethatidentifiesFoxNewsomittingthestoryifthere

existedan“importantstory”butFoxNewsdidnotreportonit.Ialsocreatesimilarlydefinedindicatorsfor

othernetworksomittingthe“importantstory.”

30

As discussed earlier, across all categories and networks, Fox seems to omit stories that are harmful for

Republicansthemost.CNNandMSNBComitsomestoriesharmfulforDemocrats(comparedtoFoxNews),but

theystillomitthematalesserratethantheyomitstoriesharmfulforRepublicans.Omissionratesforneutral

storiesareuniversallyratherhigh,corroboratingthehypothesisthatthenetworksaremutuallydifferentiating

theircontent in thecaseofnon-political stories. It is important tonote that thedata forMSNBCare lower

quality,sotheiromissionratesmightnotbeentirelyreliable.However,theydoseemquitesimilartotheones

CNNproduces.

Iusethismeasureofomissiontoconductmyinstrumentalvariables(two-stageleast-squares)analysis.Ifirst

regress the viewership of Fox News on the presence of a Nascar race. I then conduct the second-stage

regression.

ThemeanviewershipforFoxNewsinthesampleis15.3million.ThefirststagesuggeststhatNascarraces,as

wellasweekends,havedramaticnegativeeffectsonFoxNewsviewership.Nascarracesareassociatedwith

4.8millionfewerFoxNewsviewer.ThisisalmostequaltoonestandarddeviationreductioninFoxviewers—

the standarddeviation is 5.4million viewers.This result is very encouraging as it suggests that there is a

statisticallysignificantandlargereductioninFoxNewsviewershiponthedayswhenthereisaNascarrace.

31

Given thatomission is abinaryvariable, Iusebothprobit and logistic regression toproduce theestimate.

However,bothregressionsproducecoefficientsthatareeffectivelyzero.Whilebothcoefficientsaretechnically

positive,andtheprobitoneisstatisticallysignificant(theerrorsarequitesmallinbothcases),themagnitude

issominisculethatitshouldlikelybeinterpretedasazero.Furthermore,Table11indicatesthatwhenstories

harmful forDemocratsareexamined, the coefficients remaineffectively zero.While the results forneutral

storiesarenotreportedhereforthesakeofbrevity,therealsodoesnotseemtobeanychangeinFoxNews’

omissivebehavior.Ifweaccepttheinstrumentasvalid,thissuggeststhatFoxalsodoesnottrytoreporton

softnewsstoriesmorewhenitlosesviewerstoNascar.

WecanalsoexamineCNN’sviewershipandCNN’somissivebehavioronthedaysofNascarraces.Itseemsthat

Nascarraces(controllingforitbeingaweekend)arealsoassociatedwithastatisticallysignificantreductionin

CNNviewership.CNNonaveragehasa smalleraudience thanFoxNews— it is6.9millionviewersonan

averageday.However,controllingforweekends,therebeingNascarracesconstitutesa31.7%reductionin

viewershipforFoxNews,whileforCNNitisa16.4%reduction.Thissuggeststhatweretainsomeconfidence

initasaninstrument.Furthermore,whilethisregressionisnotreportedhereforbrevity,,usingNascarraces

asaninstrumentforCNNviewershipsimilarlyproducesnochangeinCNN’somissivebehavior,regardlessof

32

whetherthestoriesexaminedareharmfulforDemocratsorforRepublicans.Whilethiscontradictstheidea

thatNascarracesareashockuniquetoFoxNews,themagnitudeoftheshocktoCNNissubstantiallysmaller,

leadingtoonly1.8millionfewerviewers.Thismakessense,asitisnotRepublicansexclusivelywhowatch

Nascar,butitisexpectedthattheyconstituteamajorityoftheaudience.Whileitwouldbeidealifanaudience

groupthatsimplydoesnothaveaninterestinNascaratallexisted,thisdoesnotseemtobethecase,sowhile

CNNcannotbeusedasaplacebotomorethoroughlyexaminethevalidityoftheinstrument(andalsotheidea

thatFoxwouldgoafterCNN’sconsumers),theresultsofTable12arenonethelessencouraging.Ideally,Iwould

liketoaccessdataonindividualconsumerchoicesonwhattowatchonthosedays,butunfortunatelysuchdata

areextremelycostprohibitive1.Withtheinformationavailableatthemoment,itseemsthatFoxsuffersmore

fromNascarraces,whichshouldbemoreincentivizingforthemtoattemptreachingotheraudiences.While

NascaralsoseemstohurtCNN’sviewership,soFoxperhapswouldnottrytoreachthoseconsumers,thefact

thatitdoesnotrespondbyreportingonsoftnewsmoreeitherismorepersuasiveoftherebeingatruezero

effect.

Itseemsthatchangesinviewership,asinstrumentedforusingNascarraces,donotproduceachangeinthe

omissivebehaviorofthenetworks.Wecannotbeentirelycertainthattheexclusionrestrictionissatisfied,i.e.

that Nascar races affect Fox News’ omissive behavior regarding stories bad for Republicans only through

changesinviewership(anissuediscussedinsection5atlength).However,theydoaffectFoxNews’viewership

1 Nielsen has data that might be at least somewhat illuminating about this, but they demanded $10,000 just for aggregated daily viewership numbers for the time period. I instead obtained the dataset myself by scraping a number of AdWeek’s pages.

33

significantly,andyet,seemtogeneratenochangeswhatsoeverinFox’somissivebehavior.Thefactthattheir

associatedeffectispreciselyzeroandthecoefficienthassmallstandarderrorsindicatesthereshouldbeless

ofaconcernfortheinstrumentgeneratingbias.

ThisdoesraisethequestionofwhetherashocksuchasNascarracesissufficienttogeneratealargeenough

changeinFoxNews’behavior.WhileNascarracesaresportseventsthatlastalongtimeandgeneratelarge

changesinviewership,perhapstheyarestillnotdramaticenoughforFoxto(temporarily)changeitsstrategy.

ThismightmeanthatonlyeventssuchasperhapsOlympicGames,whichproducemoreconcentratedandalso

long-lasting(onadailylevel)distractionsfornewsviewers,aremoreappropriate.Unfortunately,thecrucial

datasetofchyronsonlybeginsin2017,whereasthelastOlympicGameswerein2016.However,inthefuture,

itwillbepossibletoinvestigatethisusingsuchastrategy.

However,regardlessofwhethertheOlympicGamesproducechangesinFox’sbehavior,thefactthatitdoesnot

seemtorespondtoNascar-induceddropsinviewershipisimportant.Arguably,asthedropinviewershipis

dramaticforFox,andmoresothanforCNN,andyetproducesnochangesinFox’somissionofanykindsof

stories(regardlessofwhethertheyharmDemocrats,Republicans,orareneutral),itispossiblethatFox(but

alsotheothernetworks)aresimplynotentirelyresponsivetoconsumerdemand.Itseemsplausible,giventhe

findingspresented, that theyhavea consistent reporting strategy theyadhere to, that isbroadlybasedon

audiencedemands,butthatnotallofitsextremeomissive(orspin-like,inthecaseofthecaravanofCentral

Americanimmigrants,forexample)behaviorisentirelydemand-driven.Ontheotherhand,whetherFoxNews’

insensitivityisinpartdrivenbypressuresfromtheRepublicanpartyremainstobeinvestigated.

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7. Conclusion

Iexaminedthesupplyofnewsstoriesontelevisionandhowtheprocessofpoliticalslantingmanifestsitself

throughomissionofstorieswithapartisancharacter.IuseanoveldatasetofTVchyrons,thetextatthebottom

ofthescreenduringabroadcast,toexamineanumberofissuesthatproducedstoriesofrelevancein2018.I

findthattherearesubstantialdifferencesinthecoverageofstorieswithpartisanvalue,thatareharmfulfor

eitherparty,butalsodiscoverindicationsofnetworksdifferentiatingtheircoverageofsoftnewstopics.Ialso

find that the attention that CongressionalRepublicans andDemocrats pay to those stories is predictive of

whetherastoryisrelayedonparticularchannels.ItheninvestigatewhetherNascarrace-inducedreductions

inFoxNewsviewershippromptthenetworktochangeitsbehavior.IdonotfindFoxNewstoomitfewerstories

harmfulforRepublicansorstoriesthatarepoliticallyneutral.FoxNews,buttheothernetworksaswell,seems

unresponsivetothesekindsofchangesinaudiencedemand.

35

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36

APPENDIX

Figure1:DistributionofNetworkandCongressionalRatiosforStoriesAboutMichaelCohen

Figure2:ExampleofSentimentAnalysis