Applications of Data-Centric Science to Social Design: Qualitative and Quantitative Understanding of Collective Human Behavior PDF
Preview Applications of Data-Centric Science to Social Design: Qualitative and Quantitative Understanding of Collective Human Behavior
Agent-Based Social Systems 14 Aki-Hiro Sato Editor Applications of Data-Centric Science to Social Design Qualitative and Quantitative Understanding of Collective Human Behavior Agent-Based Social Systems Volume 14 EditorinChief HiroshiDeguchi,Yokohama,Japan SeriesEditors Shu-HengChen,Taipei,Taiwan ClaudioCioffi-Revilla,Fairfax,USA NigelGilbert,Guildford,UK HajimeKita,Kyoto,Japan TakaoTerano,Yokohama,Japan KyoichiKijima,Tokyo,Japan SetsuyaKurahashi,Tokyo,Japan ManabuIchikawa,Saitama,Japan ShingoTakahashi,Tokyo,Japan MotonariTanabu,Yokohama,Japan Aki-HiroSato,Yokohama,Japan This series is intended to further the creation of the science of agent-based social systems, a field that is establishing itself as a transdisciplinary and cross-cultural science. The series will cover a broad spectrum of sciences, such as social sys- tems theory, sociology, business administration, management information science, organizationscience,computationalmathematicalorganizationtheory,economics, evolutionary economics, international political science, jurisprudence, policy sci- ence, socioinformation studies, cognitive science, artificial intelligence, complex adaptivesystemstheory,philosophyofscience,andotherrelateddisciplines. The series will provide a systematic study of the various new cross-cultural arenas of the human sciences. Such an approach has been successfully tried several times in the history of the modern science of humanities and systems and has helped to create such important conceptual frameworks and theories as cybernetics, synergetics, general systems theory, cognitive science, and complex adaptivesystems. Wewanttocreateaconceptualframeworkanddesigntheoryforsocioeconomic systemsofthetwenty-firstcenturyinacross-culturalandtransdisciplinarycontext. Forthispurposeweplantotakeanagent-basedapproach.Developedoverthelast decade, agent-based modeling is a new trend within the social sciences and is a child of the modern sciences of humanities and systems. In this series the term “agent-based” is used across a broad spectrum that includes not only the classical usage of the normative and rational agent but also an interpretive and subjective agent. We seek the antinomy of the macro and micro, subjective and rational, functional and structural,bottom-up and top-down, global and local, and structure and agency within the social sciences. Agent-based modeling includes both sides oftheseopposites.“Agent”isourgroundingformodeling;simulation,theory,and realworldgroundingarealsorequired. As an approach, agent-based simulation is an important tool for the new experimentalfieldsofthesocialsciences;itcanbeusedtoprovideexplanationsand decision support for real-world problems, and its theories include both conceptual andmathematicalones.Aconceptualapproachisvitalforcreatingnewframeworks of the worldview, and the mathematical approach is essential to clarify the logical structureofanynewframeworkormodel.Explorationofseveraldifferentwaysof real-world grounding is required for this approach. Other issues to be considered intheseriesincludethesystemsdesignofthiscentury’sglobalandlocalsocioeco- nomicsystems. Moreinformationaboutthisseriesathttp://www.springer.com/series/7188 Aki-Hiro Sato Editor Applications of Data-Centric Science to Social Design Qualitative and Quantitative Understanding of Collective Human Behavior 123 Editor Aki-HiroSato YokohamaCityUniversity Kanazawa-ku,Yokohama-shi, Kanagawa,Japan JapanScienceandTechnologyAgencyPRESTO Kawaguchi-shi,Saitama,Japan StatisticalResearchandTrainingInstitute, MinistryofInternalAffairsandCommunications Shinjuku-ku,Tokyo,Japan ISSN1861-0803 Agent-BasedSocialSystems ISBN978-981-10-7193-5 ISBN978-981-10-7194-2 (eBook) https://doi.org/10.1007/978-981-10-7194-2 ©SpringerNatureSingaporePteLtd.2019 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpartof thematerialisconcerned,specificallytherightsoftranslation,reprinting,reuseofillustrations,recitation, broadcasting,reproductiononmicrofilmsorinanyotherphysicalway,andtransmissionorinformation storageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilarmethodology nowknownorhereafterdeveloped. Theuseofgeneraldescriptivenames,registerednames,trademarks,servicemarks,etc.inthispublication doesnotimply,evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfromtherelevant protectivelawsandregulationsandthereforefreeforgeneraluse. Thepublisher,theauthors,andtheeditorsaresafetoassumethattheadviceandinformationinthisbook arebelievedtobetrueandaccurateatthedateofpublication.Neitherthepublishernortheauthorsor theeditorsgiveawarranty,expressorimplied,withrespecttothematerialcontainedhereinorforany errorsoromissionsthatmayhavebeenmade.Thepublisherremainsneutralwithregardtojurisdictional claimsinpublishedmapsandinstitutionalaffiliations. ThisSpringerimprintispublishedbytheregisteredcompanySpringerNatureSingaporePteLtd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore Preface This book aims to understand human behavior and to address methods for social designfrombothqualitativeandquantitativeperspectivesbasedonthemethodology of data-centric science. Recently, a large amount of data formatted by various expressionsareaccumulatedindifferentfieldsofsocioeconomicsystems.However, at this moment, it seems that the utilization of such data has not been matured, yet.Since data arenot answers butquestions inspiringpeople who areworking in the fields, many efforts of data analysis are required to obtain insights from data. Furthermore,theoutcomesofdataanalysisshouldsupporthumandecision-making fromqualitativeandquantitativepointsofview. The design process is a sequence of actions with the decision-making. There mustbealotofusefulpointsofdata-centricsciencetodesign.Primarily,thisbook hasbeeneditedbymotivatingtocollectmethodologiesandpracticalexamplesfor contributing to data-driven social design. The intentions behind this book are to develop the methodology to support people who are joining or attempt to join all theactivitiesrelatedto“socialdesign”basedondata. Thisbookcontainsthreemainparts,suchas: PartI:Methodsfordataanalysisanddesign PartII:Amathematicalfoundationofcollectivehumanbehavior PartIII:Applicationsofdataanalysistosocialdesign Part I mentions a conceptual framework of applications of data-centric science tosocialdesignandincludesfourchapters.Readersmayfindmethodologicalideas andframeworksthatcanbeusedwhentheyconsiderdesignforsocialsystemsfrom thechaptersinPartI. Thechaptertitled“HowtoDesignSocietyfromaData-CentricPointofView” by Aki-Hiro Sato explains the intentions behind this book including the three types of aspects: human behavior, data-centric science, and social design. The chapter titled “Practical Methods for Data Analysis” by Aki-Hiro Sato explains practical methods used in data utilization. The data analysis is an essential part to understand the phenomena observed in the actual environment. The data analysis formsaworkflowconsistingofdataacquisition,datacollection,datavisualization, v vi Preface and quantification and data interpretation. The purpose of data analysis is to find insightsonphenomenathatwehaveattendedtoandmakedecision-makerschange their behavior. The chapter titled “An Approach to Product Design Involving HeterogeneousStakeholders”byAki-HiroSatodiscusseshowtodesignourproduct regarding data and communications among multi-stakeholders. Several methods to design our product as group work are addressed. Specifically, eight techniques that can be used in the group work are introduced step by step. The chapter titled “Designing Human-Machine Systems Focusing on Benefits of Inconvenience” by HiroshiKawakamiproposesbenefitsofinconvenienceinhuman-machinesystems topreventlossofhumanabilityandjoyintooconvenienthuman-machinesystems. Part II introduces collective human behavior and information cascade in social groups from a mathematical physics point of view. Collective human behavior is oftenseeninsocioeconomicsystemsandshouldbeunderstoodwhenreaderswant todealwithsocioeconomicsystemsinvolvingheterogeneousstakeholders.Readers can understand collective human behavior with information interactions from the chaptersinthispart. The chapter titled “Information Cascade and Phase Transition” by Masato Hisakado and Shintaro Mori discusses a voting model with two candidates and concludes that the model features a phase transition beyond which a state where most voters make the correct choice coexists with one where most of them are wrongasthefractionofherdersincreases;thechaptertitled“InformationCascade, Kirman’s Ant Colony Model, and Kinetic Ising Model” by Masato Hisakado and Shintaro Mori discusses a voting model in which voters can obtain information from a finite number of previous voters. In this case, the phase transition can be observed in infinite-size limit, but no phase transition happens when the reference numberisfinite.Thechaptertitled“InformationCascadeandNetworks”byMasato Hisakado and Shintaro Mori discusses a voting model on networks and concludes thattheinfluenceofnetworkscanbeseenintheconvergencespeedonlyandcannot be seen in the information cascade transition. The chapter titled “The Pitman-Yor Process and Choice Behavior” by Masato Hisakado and Shintaro Mori discusses choicebehaviorusingavotingmodelinwhichvoterscanobtaininformationfrom a finite number of some previous voters and concludes that the posting process is describedbytheproposedmodelforanalogherdersforasmallreferencenumber. The chapter titled “Domino Effect in Information Cascade” by Shintaro Mori and Masato Hisakado studies several simple models for information cascade and proposes that the memory length in the sequential decisions and the number of stablestates(equilibrium)playthekeyroleinthedominoeffectintheinformation cascade.Thechaptertitled“InformationCascadeExperiment:GeneralKnowledge Quiz” by Shintaro Mori and Masato Hisakado and the chapter titled “Information CascadeExperiment:UrnQuiz”byShintaroMoriandMasatoHisakadodealwith information cascade experiments. The difficulty of the questions depends on the sequential collective behavior. The chapter titled “Information Cascade and Bayes Formula” by Masato Hisakado and Shintaro Mori considers a voting experiment using two-choice questions and attempts to establish the Bayes formula to correct thewrongdecisions. Preface vii Part III provides readers with several case studies of social systems based on a data-driven approach. The final four chapters provide useful insights and domain knowledgeineachcasestudy.Readersmayobtaininsightsanddomainknowledge to deepen understandings of socioeconomic systems from data analysis. These chapters may be useful when they obtain domain knowledge, practical examples, need specification, and design of socioeconomic systems. All chapters are useful whenreadersattempttosolvesocialissuesanddealwithsocialdesignbyusingthe methodologyofdata-centricscience. Thechaptertitled“HowBettersVoteinHorseRaceBettingMarket”byShintaro Mori and Masato Hisakado analyzes JRA (Japan Racing Association) win betting data and how the efficiency and the accuracy improve as betting proceeds. The chapter titled “Smart Micro-sensing: Reaching Sustainability in Agriculture via DistributedSensorsintheFoodChain”byRobDolciandLauraBoschisproposes a method to detect contaminants during the whole food supply chain by using portablebiosensordevices.Theproposedmethodcanimprovefoodsafetyinboth agricultureandfoodindustries.Thechaptertitled“High-FrequencyDataAnalysis ofForeignExchangeMarkets”byAki-HiroSatoproposesamethodtocharacterize collectivehumanbehaviorbasedonamultivariatePoissonmodelandshowsresults obtained from empirical analysis with high-frequency foreign exchange data. The common mode may measure collective human behavior from observable activity data.Thechaptertitled“OnMeasuringExtremeSynchronywithNetworkEntropy ofBipartiteGraphs”byAki-HiroSatoproposesamethodtoquantifythestructure of a bipartite graph using a network entropy per link. The network entropy on a bipartite network per link was used to quantify the degree of collective behavior in the foreign exchange market. The proposed method is applicable to detecting extremesynchronyinvarioustypesofsocioeconomicsystems. This book will be devoted to promoting data-driven social design with multi- stakeholdersthroughdesignactivitiesconsistingofdataacquisition,datacollection, data analysis, data interpretation, reporting, and decision-making by accumulating data,methods,andconnectionswithstakeholders. Yokohama,Japan Aki-HiroSato Contents PartI MethodsforDataAnalysisandDesign HowtoDesignSocietyfromaData-CentricPointofView.................. 3 Aki-HiroSato PracticalMethodsforDataAnalysis........................................... 17 Aki-HiroSato AnApproachtoProductDesignInvolvingHeterogeneous Stakeholders...................................................................... 33 Aki-HiroSato Designing Human-Machine Systems Focusing on Benefits ofInconvenience.................................................................. 51 HiroshiKawakami PartII MathematicalFoundationofHumanCollectiveBehavior InformationCascadeandPhaseTransition................................... 65 MasatoHisakadoandShintaroMori InformationCascade,Kirman’sAntColonyModel,andKinetic IsingModel ....................................................................... 81 MasatoHisakadoandShintaroMori InformationCascadeandNetworks ........................................... 99 MasatoHisakadoandShintaroMori ThePitman-YorProcessandChoiceBehavior ............................... 119 MasatoHisakadoandShintaroMori DominoEffectinInformationCascade........................................ 141 ShintaroMoriandMasatoHisakado InformationCascadeExperiment:GeneralKnowledgeQuiz .............. 167 ShintaroMoriandMasatoHisakado ix x Contents InformationCascadeExperiment:UrnQuiz................................. 181 ShintaroMoriandMasatoHisakado InformationCascadeandBayesFormula..................................... 193 MasatoHisakadoandShintaroMori PartIII ApplicationsofDataAnalysistoSocialDesign HowBettersVoteinHorseRaceBettingMarket............................. 205 ShintaroMoriandMasatoHisakado Smart Micro-sensing: Reaching Sustainability in Agriculture viaDistributedSensorsintheFoodChain.................................... 217 R.DolciandL.Boschis High-FrequencyDataAnalysisofForeignExchangeMarkets ............. 225 Aki-HiroSato On Measuring Extreme Synchrony with Network Entropy ofBipartiteGraphs .............................................................. 247 Aki-HiroSato
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