media bias on television and its determinants
TRANSCRIPT
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
18
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
20
storiesabouttheissue.Forexample,attheverypeakofcoverageofMichaelCohen,thereisanextremelyhigh
numberofmorethan400chyronsperdaydevotedtothestoryonCNN.Incontrast,Foxdevotesamere50
chyronstothestorythatday.
Figure2:NewsCoverageofMichaelCohen
Figure3:NewsCoverageofIllegalImmigration
21
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
22
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.
24
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.
29
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.
34
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
References
Mullainathan,S.,Shleifer,A.(2005)TheMarketforNews.AmericanEconomicReview95(1):1031-1053.
Gentzkow, M., Shapiro, J. (2010). What Drives Media Slant? Evidence from U.S. Daily Newspapers.Econometrica,78(1).doi:10.3386/w12707
Groseclose,T.Milyo,J.(2005)AMeasureofMediaBias.TheQuarterlyJournalofEconomics120(4)
Durante R., Zhuravskaya K. (2016) Attack When the World is not Watching? U.S. News and the Israeli-PalestinianConflict.JournalofPoliticalEconomy
DuranteR.,PinottiP.,TeseiA.(2019)ThePoliticalLegacyofEntertainmentTV.AmericanEconomicReview109(7)2497-2530
DellaVigna,S. andKaplan,E. (2007)TheFoxNewsEffect:MediaBiasandVoting.TheQuarterly JournalofEconomics1221187-1234.
Martin,G.Yurukoglu,A.(2017)BiasinCableNews:PersuasionandPolarization.AmericanEconomicReview107(9)2565-99
ThirdEye:APIforTVNewsArchivechyrons.(n.d.).Retrievedfromhttps://archive.org/services/third-eye.phpEshelman,R.(n.d.).Thedangeroffairandbalanced
Kalhoefer,K.(2017,March16).HowBroadcastNetworksCoveredClimateChangeIn2016.
Nuccitelli,D.(2018,April05).Americanconservativesarestillcluelessaboutthe97%expertclimateconsensus
StrombergD.,Snyder,J.(2008)PressCoverageandPoliticalAccountability.NBERWorkingPaper
Prat,A.,Kennedy,P.(2019)WhereDoPeopleGetTheirNews?.EconomicPolicy34(97)5-47
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APPENDIX
Figure1:DistributionofNetworkandCongressionalRatiosforStoriesAboutMichaelCohen
Figure2:ExampleofSentimentAnalysis