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OUPCORRECTEDPROOF–FINAL,24/11/2015,SPi THE CONNECTED PAST OUPCORRECTEDPROOF–FINAL,24/11/2015,SPi OUPCORRECTEDPROOF–FINAL,24/11/2015,SPi The Connected Past Challenges to Network Studies in Archaeology and History Edited by TOM BRUGHMANS, ANNA COLLAR, AND FIONA COWARD 1 OUPCORRECTEDPROOF–FINAL,24/11/2015,SPi 3 GreatClarendonStreet,Oxford,OX26DP, UnitedKingdom OxfordUniversityPressisadepartmentoftheUniversityofOxford. ItfurtherstheUniversity’sobjectiveofexcellenceinresearch,scholarship, andeducationbypublishingworldwide.Oxfordisaregisteredtrademarkof OxfordUniversityPressintheUKandincertainothercountries ©OxfordUniversityPress2016 Themoralrightsoftheauthorshavebeenasserted FirstEditionpublishedin2016 Impression:1 Allrightsreserved.Nopartofthispublicationmaybereproduced,storedin aretrievalsystem,ortransmitted,inanyformorbyanymeans,withoutthe priorpermissioninwritingofOxfordUniversityPress,orasexpresslypermitted bylaw,bylicenceorundertermsagreedwiththeappropriatereprographics rightsorganization.Enquiriesconcerningreproductionoutsidethescopeofthe aboveshouldbesenttotheRightsDepartment,OxfordUniversityPress,atthe addressabove Youmustnotcirculatethisworkinanyotherform andyoumustimposethissameconditiononanyacquirer PublishedintheUnitedStatesofAmericabyOxfordUniversityPress 198MadisonAvenue,NewYork,NY10016,UnitedStatesofAmerica BritishLibraryCataloguinginPublicationData Dataavailable LibraryofCongressControlNumber:2015943401 ISBN 978–0–19–874851–9 PrintedinGreatBritainby ClaysLtd,StIvesplc LinkstothirdpartywebsitesareprovidedbyOxfordingoodfaithand forinformationonly.Oxforddisclaimsanyresponsibilityforthematerials containedinanythirdpartywebsitereferencedinthiswork. OUPCORRECTEDPROOF–FINAL,24/11/2015,SPi Contents ListofFigures vii ListofTables xi ListofContributors xiii PART I: CHALLENGING NETWORK METHODS AND THEORIES 1. NetworkPerspectivesonthePast:TacklingtheChallenges 3 TomBrughmans,AnnaCollar,andFionaCoward 2. NetworksinArchaeology:BetweenScientificMethodand HumanisticMetaphor 21 CarlKnappett 3. NetworksorWork-nets?Actor-NetworkTheoryandMultiple SocialTopologiesintheProductionofRomanTerraSigillata 35 AstridVanOyen PART II: CHALLENGING NETWORK ANALYSIS OF ARCHAEOLOGICAL AND HISTORICAL DATA 4. AnalyticalChallengesfortheApplicationofSocialNetwork AnalysisinArchaeology 59 MatthewA.Peeples,BarbaraJ.Mills,W.RandallHaas,Jr, JefferyJ.Clark,andJohnM.Roberts,Jr 5. HowReliableareCentralityMeasuresforDataCollectedfrom FragmentaryandHeterogeneousHistoricalSources?ACaseStudy 85 MartenDüring 6. UncoveringtheHiddenRoutes:AlgorithmsforIdentifying PathsandMissingLinksinTradeNetworks 103 ConstantinosTsirogiannisandChristosTsirogiannis PART III: CHALLENGING NETWORK MODELS 7. CanArchaeologicalModelsAlwaysFulfilourPrejudices? 123 RayRivers OUPCORRECTEDPROOF–FINAL,24/11/2015,SPi vi Contents 8. WhichNetworkModelShouldIUse?TowardsaQuantitative ComparisonofSpatialNetworkModelsinArchaeology 149 TimEvans 9. Networks,Homophily,andtheSpreadofInnovations 175 AnneKandlerandFabioCaccioli Index 199 OUPCORRECTEDPROOF–FINAL,24/11/2015,SPi List of Figures 1.1. Anabstractrepresentationofanetworkmodelandan exampleofhowanetworkmodelisusedtoexplorea particularphenomenon. 8 1.2. Differentdatatypesrepresentingindividualsandsocial relationships. 9 4.1. MapoftheSouthwestSocialNetworksProjectstudyarea. 61 4.2. Overviewoftheceramicapportioningprocedure. 68 4.3. NetworkdiagramsforthesouthernSouthwestforthe AD1300–1350andAD1350–1400intervals. 70 4.4. NetworkdiagramofthegreaterHohokamregionforthe AD1250–1300,1300–1350,and1350–1400intervals. 72 4.5. NetworkdiagramsoftheentireSouthwestSocialNetworksProject studyareafortheAD1250–1300,1300–1350,1350–1400,and 1400–1450intervals. 73 4.6. Correlationsbetweendegreecentralityinfullnetworkfor each50-yearintervalandsub-samplesatsampling fractionsfrom90%to10%oftotal. 76 4.7. Correlationsbetweeneigenvectorcentralityinfullnetwork foreach50-yearintervalandsub-samplesatsampling fractionsfrom90%to10%oftotal. 76 5.1. Matchesbetweeninfluentialactorsandcentralityscores. 96 5.2. Mappinginfluentialactorswithintheirnetworks. 98 6.1. Theundirectedversionofthenetworkextractedfrom WatsonandTodeschini(2007). 107 6.2. Thedirectedversionofthenetworkextractedfrom WatsonandTodeschini(2007). 108 6.3. Thepathsubnetworkbetweenthenodethatcorresponds toRobertHechtandthenodethatcorrespondstothe GettyMuseum. 110 6.4. Theperformanceofthetwomethodsthatindicate missinglinksinthenetwork. 118 7.1. ImportantMBAsitesfortheSouthernAegean. 136 7.2. Testingthesensitivityofthesimplegravitymodeland thedoublyconstrainedgravitymodeltothedistance scaleforsinglejourneys. 138 OUPCORRECTEDPROOF–FINAL,1/12/2015,SPi viii ListofFigures 7.3. ExemplaryariadnenetworksforD=100kmbeforeand aftertheeruptionofThera. 140 7.4. The109archaicsettlementsbasedonfigure1from RihllandWilson(1987)andusingthesamelabels. 142 8.1. FourMinoansitesusedforexamples,indicatingthe directroutestoandfromKnossosandthequickest routes. 151 8.2. Twosimplenetworksderivedusingthequickestdistances: theMDNnetworkfora110 kmcutoff,andthePPAk=1network. 154 8.3. IllustrationoftheflowF fromsitestositet. 157 st 8.4. Illustrationoftypicalformsforthedeterrencefunction f asafunctionofthedistancebetweentwosites. 158 st 8.5. Anartificiallayoutoffortytestsites,arrangedinfour groupsoften. 163 8.6. Theresultsofprincipalcomponentanalysisofacomparison oftheMDNmodelontheartificialfourgroupsof10sites. 165 8.7. HierarchicalclusteringofacomparisonoftheMDNmodel ontheartificialfourgroupsof10sites. 166 8.8. Scatterplotofthefirsttwocomponentsofthevertex vectorsforsevenmodelsusingtestdatasites. 168 8.9. Thesimilaritybetweensevenedgemodelsproducing thesameaverageweighteddistanceofΔ=57 km. 169 9.1. Exampleofapopulationorganizedinarandomnetwork. 178 9.2. Spreadingprobabilityandfinalcascadesizeinthe WattsmodelwithN=10000andf=f=0.16. 180 i 9.3. Spreadingprobabilitiesandcorrespondingaveragecascade sizeofthehigh-statusandlow-statussubpopulations, whentheinnovationisintroducedbyahigh-statusand byalow-statusindividual. 183 9.4. Fractionsofthehigh-statusandlow-statussubpopulations thathaveadoptedtheinnovationatdifferenttimesteps. 184 9.5. RelationshipbetweentheparameterJandthenetworkcorrelation. 187 9.6. Spreadingprobabilitiesandcorrespondingaveragecascade sizeofthehigh-statusandlow-statussubpopulations,when theinnovationisintroducedbyahigh-statusindividual. 188 9.7. Spreadingprobabilitiesandcorrespondingaveragecascade sizeofthehigh-statusandlow-statussubpopulations, whentheinnovationisintroducedbyalow-statusindividual. 189 OUPCORRECTEDPROOF–FINAL,24/11/2015,SPi ListofFigures ix 9.8. Fractionsofthehigh-statusandlow-statussubpopulations andcorrespondingfractionsofwholepopulationwhich haveadoptedtheinnovationatdifferenttimesteps. 190 9.9. Spreadingprobabilitiesforthehigh-statusandlow-status subpopulationsforvaryingthemeasureofnetworkcorrelation. 190

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One of the most exciting recent developments in archaeology and history has been the adoption of new perspectives which see human societies in the past--as in the present--as made up of networks of interlinked individuals. This view of people as always connected through physical and conceptual netwo
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OUPCORRECTEDPROOF–FINAL,24/11/2015,SPi THE CONNECTED PAST OUPCORRECTEDPROOF–FINAL,24/11/2015,SPi OUPCORRECTEDPROOF–FINAL,24/11/2015,SPi The Connected Past Challenges to Network Studies in Archaeology and History Edited by TOM BRUGHMANS, ANNA COLLAR, AND FIONA COWARD 1 OUPCORRECTEDPROOF–FINAL,24/11/2015,SPi 3 GreatClarendonStreet,Oxford,OX26DP, UnitedKingdom OxfordUniversityPressisadepartmentoftheUniversityofOxford. ItfurtherstheUniversity’sobjectiveofexcellenceinresearch,scholarship, andeducationbypublishingworldwide.Oxfordisaregisteredtrademarkof OxfordUniversityPressintheUKandincertainothercountries ©OxfordUniversityPress2016 Themoralrightsoftheauthorshavebeenasserted FirstEditionpublishedin2016 Impression:1 Allrightsreserved.Nopartofthispublicationmaybereproduced,storedin aretrievalsystem,ortransmitted,inanyformorbyanymeans,withoutthe priorpermissioninwritingofOxfordUniversityPress,orasexpresslypermitted bylaw,bylicenceorundertermsagreedwiththeappropriatereprographics rightsorganization.Enquiriesconcerningreproductionoutsidethescopeofthe aboveshouldbesenttotheRightsDepartment,OxfordUniversityPress,atthe addressabove Youmustnotcirculatethisworkinanyotherform andyoumustimposethissameconditiononanyacquirer PublishedintheUnitedStatesofAmericabyOxfordUniversityPress 198MadisonAvenue,NewYork,NY10016,UnitedStatesofAmerica BritishLibraryCataloguinginPublicationData Dataavailable LibraryofCongressControlNumber:2015943401 ISBN 978–0–19–874851–9 PrintedinGreatBritainby ClaysLtd,StIvesplc LinkstothirdpartywebsitesareprovidedbyOxfordingoodfaithand forinformationonly.Oxforddisclaimsanyresponsibilityforthematerials containedinanythirdpartywebsitereferencedinthiswork. OUPCORRECTEDPROOF–FINAL,24/11/2015,SPi Contents ListofFigures vii ListofTables xi ListofContributors xiii PART I: CHALLENGING NETWORK METHODS AND THEORIES 1. NetworkPerspectivesonthePast:TacklingtheChallenges 3 TomBrughmans,AnnaCollar,andFionaCoward 2. NetworksinArchaeology:BetweenScientificMethodand HumanisticMetaphor 21 CarlKnappett 3. NetworksorWork-nets?Actor-NetworkTheoryandMultiple SocialTopologiesintheProductionofRomanTerraSigillata 35 AstridVanOyen PART II: CHALLENGING NETWORK ANALYSIS OF ARCHAEOLOGICAL AND HISTORICAL DATA 4. AnalyticalChallengesfortheApplicationofSocialNetwork AnalysisinArchaeology 59 MatthewA.Peeples,BarbaraJ.Mills,W.RandallHaas,Jr, JefferyJ.Clark,andJohnM.Roberts,Jr 5. HowReliableareCentralityMeasuresforDataCollectedfrom FragmentaryandHeterogeneousHistoricalSources?ACaseStudy 85 MartenDüring 6. UncoveringtheHiddenRoutes:AlgorithmsforIdentifying PathsandMissingLinksinTradeNetworks 103 ConstantinosTsirogiannisandChristosTsirogiannis PART III: CHALLENGING NETWORK MODELS 7. CanArchaeologicalModelsAlwaysFulfilourPrejudices? 123 RayRivers OUPCORRECTEDPROOF–FINAL,24/11/2015,SPi vi Contents 8. WhichNetworkModelShouldIUse?TowardsaQuantitative ComparisonofSpatialNetworkModelsinArchaeology 149 TimEvans 9. Networks,Homophily,andtheSpreadofInnovations 175 AnneKandlerandFabioCaccioli Index 199 OUPCORRECTEDPROOF–FINAL,24/11/2015,SPi List of Figures 1.1. Anabstractrepresentationofanetworkmodelandan exampleofhowanetworkmodelisusedtoexplorea particularphenomenon. 8 1.2. Differentdatatypesrepresentingindividualsandsocial relationships. 9 4.1. MapoftheSouthwestSocialNetworksProjectstudyarea. 61 4.2. Overviewoftheceramicapportioningprocedure. 68 4.3. NetworkdiagramsforthesouthernSouthwestforthe AD1300–1350andAD1350–1400intervals. 70 4.4. NetworkdiagramofthegreaterHohokamregionforthe AD1250–1300,1300–1350,and1350–1400intervals. 72 4.5. NetworkdiagramsoftheentireSouthwestSocialNetworksProject studyareafortheAD1250–1300,1300–1350,1350–1400,and 1400–1450intervals. 73 4.6. Correlationsbetweendegreecentralityinfullnetworkfor each50-yearintervalandsub-samplesatsampling fractionsfrom90%to10%oftotal. 76 4.7. Correlationsbetweeneigenvectorcentralityinfullnetwork foreach50-yearintervalandsub-samplesatsampling fractionsfrom90%to10%oftotal. 76 5.1. Matchesbetweeninfluentialactorsandcentralityscores. 96 5.2. Mappinginfluentialactorswithintheirnetworks. 98 6.1. Theundirectedversionofthenetworkextractedfrom WatsonandTodeschini(2007). 107 6.2. Thedirectedversionofthenetworkextractedfrom WatsonandTodeschini(2007). 108 6.3. Thepathsubnetworkbetweenthenodethatcorresponds toRobertHechtandthenodethatcorrespondstothe GettyMuseum. 110 6.4. Theperformanceofthetwomethodsthatindicate missinglinksinthenetwork. 118 7.1. ImportantMBAsitesfortheSouthernAegean. 136 7.2. Testingthesensitivityofthesimplegravitymodeland thedoublyconstrainedgravitymodeltothedistance scaleforsinglejourneys. 138 OUPCORRECTEDPROOF–FINAL,1/12/2015,SPi viii ListofFigures 7.3. ExemplaryariadnenetworksforD=100kmbeforeand aftertheeruptionofThera. 140 7.4. The109archaicsettlementsbasedonfigure1from RihllandWilson(1987)andusingthesamelabels. 142 8.1. FourMinoansitesusedforexamples,indicatingthe directroutestoandfromKnossosandthequickest routes. 151 8.2. Twosimplenetworksderivedusingthequickestdistances: theMDNnetworkfora110 kmcutoff,andthePPAk=1network. 154 8.3. IllustrationoftheflowF fromsitestositet. 157 st 8.4. Illustrationoftypicalformsforthedeterrencefunction f asafunctionofthedistancebetweentwosites. 158 st 8.5. Anartificiallayoutoffortytestsites,arrangedinfour groupsoften. 163 8.6. Theresultsofprincipalcomponentanalysisofacomparison oftheMDNmodelontheartificialfourgroupsof10sites. 165 8.7. HierarchicalclusteringofacomparisonoftheMDNmodel ontheartificialfourgroupsof10sites. 166 8.8. Scatterplotofthefirsttwocomponentsofthevertex vectorsforsevenmodelsusingtestdatasites. 168 8.9. Thesimilaritybetweensevenedgemodelsproducing thesameaverageweighteddistanceofΔ=57 km. 169 9.1. Exampleofapopulationorganizedinarandomnetwork. 178 9.2. Spreadingprobabilityandfinalcascadesizeinthe WattsmodelwithN=10000andf=f=0.16. 180 i 9.3. Spreadingprobabilitiesandcorrespondingaveragecascade sizeofthehigh-statusandlow-statussubpopulations, whentheinnovationisintroducedbyahigh-statusand byalow-statusindividual. 183 9.4. Fractionsofthehigh-statusandlow-statussubpopulations thathaveadoptedtheinnovationatdifferenttimesteps. 184 9.5. RelationshipbetweentheparameterJandthenetworkcorrelation. 187 9.6. Spreadingprobabilitiesandcorrespondingaveragecascade sizeofthehigh-statusandlow-statussubpopulations,when theinnovationisintroducedbyahigh-statusindividual. 188 9.7. Spreadingprobabilitiesandcorrespondingaveragecascade sizeofthehigh-statusandlow-statussubpopulations, whentheinnovationisintroducedbyalow-statusindividual. 189 OUPCORRECTEDPROOF–FINAL,24/11/2015,SPi ListofFigures ix 9.8. Fractionsofthehigh-statusandlow-statussubpopulations andcorrespondingfractionsofwholepopulationwhich haveadoptedtheinnovationatdifferenttimesteps. 190 9.9. Spreadingprobabilitiesforthehigh-statusandlow-status subpopulationsforvaryingthemeasureofnetworkcorrelation. 190

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One of the most exciting recent developments in archaeology and history has been the adoption of new perspectives which see human societies in the past--as in the present--as made up of networks of interlinked individuals. This view of people as always connected through physical and conceptual netwo
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