Towards a Theoretical Framework for Analyzing Complex Linguistic Networks PDF
Preview Towards a Theoretical Framework for Analyzing Complex Linguistic Networks
Understanding Complex Systems Alexander Mehler Andy Lücking Sven Banisch Philippe Blanchard Barbara Frank-Job Editors Towards a Theoretical Framework for Analyzing Complex Linguistic Networks Springer Complexity SpringerComplexityisaninterdisciplinaryprogram publishingthebestresearchandacademic- level teachingonbothfundamental andappliedaspects ofcomplexsystems—cutting across all traditionaldisciplinesofthenaturalandlifesciences,engineering, economics,medicine,neuro- science,socialandcomputerscience. ComplexSystemsaresystemsthatcomprisemanyinteractingpartswiththeabilitytogenerate anewqualityofmacroscopiccollectivebehaviorthemanifestationsofwhicharethespontaneous formationofdistinctivetemporal,spatialorfunctionalstructures.Modelsofsuchsystemscanbe successfullymappedontoquitediverse“real-life”situationsliketheclimate,thecoherentemis- sion oflight from lasers, chemical reaction–diffusion systems, biological cellular networks, the dynamicsofstockmarketsandoftheinternet,earthquakestatisticsandprediction,freewaytraffic, thehumanbrain,ortheformationofopinionsinsocialsystems,tonamejustsomeofthepopular applications. Althoughtheirscopeandmethodologiesoverlapsomewhat,onecandistinguishthefollowing mainconceptsandtools:self-organization,nonlineardynamics,synergetics,turbulence,dynami- calsystems,catastrophes,instabilities,stochasticprocesses,chaos,graphsandnetworks,cellular automata,adaptivesystems,geneticalgorithmsandcomputationalintelligence. ThethreemajorbookpublicationplatformsoftheSpringerComplexityprogramarethemono- graphseries“UnderstandingComplexSystems”focusingonthevariousapplicationsofcomplex- ity,andthe“SpringerSeriesinSynergetics”,whichisdevotedtothequantitativetheoreticaland methodologicalfoundations,andthe“SpringerBriefsinComplexity”whichareconciseandtopical workingreports,case-studies,surveys,essaysandlecturenotesofrelevancetothefield.Inaddition tothebooksinthesetwocoreseries,theprogramalsoincorporatesindividualtitlesrangingfrom textbookstomajorreferenceworks. EditorialandProgrammeAdvisoryBoard HenryAbarbanel,InstituteforNonlinearScience,UniversityofCalifornia,SanDiego,USA DanBraha,NewEnglandComplexSystems,InstituteandUniversityofMassachusetts,Dartmouth,USA PéterÉrdi,CenterforComplexSystemsStudies,KalamazooCollege,USAandHungarianAcademyof Sciences,Budapest,Hungary KarlFriston,InstituteofCognitiveNeuroscience,UniversityCollegeLondon,London,UK HermannHaken,CenterofSynergetics,UniversityofStuttgart,Stuttgart,Germany Viktor Jirsa, Centre National de la Recherche Scientifique (CNRS), Université de la Méditerranée, Marseille,France JanuszKacprzyk,SystemResearch,PolishAcademyofSciences,Warsaw,Poland KunihikoKaneko,ResearchCenterforComplexSystemsBiology,TheUniversityofTokyo,Tokyo,Japan ScottKelso,CenterforComplexSystemsandBrainSciences,FloridaAtlanticUniversity,BocaRaton, USA Markus Kirkilionis, Mathematics Institute and Centre for Complex Systems, University ofWarwick, Coventry,UK JürgenKurths,NonlinearDynamicsGroup,UniversityofPotsdam,Potsdam,Germany AndrzejNowak,DepartmentofPsychology,WarsawUniversity,Poland HassanQudrat-Ullah,SchoolofAdministrativeStudies,YorkUniversity,Canada LindaReichl,CenterforComplexQuantumSystems,UniversityofTexas,Austin,USA PeterSchuster,TheoreticalChemistryandStructuralBiology,UniversityofVienna,Vienna,Austria FrankSchweitzer,SystemDesign,ETHZürich,Zürich,Switzerland DidierSornette,EntrepreneurialRisk,ETHZürich,Zürich,Switzerland StefanThurner,SectionforScienceofComplexSystems,MedicalUniversityofVienna,Vienna,Austria Understanding Complex Systems Founding Editor: Scott Kelso Futurescientificandtechnological developments inmanyfieldswillnecessarily dependuponcoming togripswithcomplexsystems.Suchsystemsarecomplexinboththeircomposition—typically many differentkindsofcomponentsinteractingsimultaneouslyandnonlinearlywitheachotherandtheirenvi- ronmentsonmultiplelevels—andintherichdiversityofbehaviorofwhichtheyarecapable. TheSpringerSeriesinUnderstandingComplexSystemsseries(UCS)promotesnewstrategiesand paradigmsforunderstandingandrealizingapplicationsofcomplexsystemsresearchinawidevarietyof fieldsandendeavors.UCSisexplicitlytransdisciplinary.Ithasthreemaingoals:First,toelaboratethe concepts,methodsandtoolsofcomplexsystemsatalllevelsofdescriptionandinallscientificfields, especiallynewlyemergingareaswithinthelife,social,behavioral,economic,neuro-andcognitivesci- ences(andderivativesthereof);second,toencouragenovelapplicationsoftheseideasinvariousfields ofengineeringandcomputationsuchasrobotics,nano-technology andinformatics;third,toprovidea singleforumwithinwhichcommonalitiesanddifferencesintheworkingsofcomplexsystemsmaybe discerned,henceleadingtodeeperinsightandunderstanding. UCSwillpublishmonographs,lecturenotesandselectededitedcontributionsaimedatcommunicat- ingnewfindingstoalargemultidisciplinaryaudience. Moreinformationaboutthisseriesathttp://www.springer.com/series/5394 · Alexander Mehler Andy Lücking · Sven Banisch Philippe Blanchard Barbara Frank-Job Editors Towards a Theoretical Framework for Analyzing Complex Linguistic Networks ABC Editors AlexanderMehler PhilippeBlanchard Goethe-UniversityFrankfurtamMain DepartmentofPhysics DepartmentofComputerScience UniversityofBielefeld andMathematics Bielefeld FrankfurtamMain Germany Germany BarbaraFrank-Job AndyLücking FacultyofLinguistics&LiteraryStudies Goethe-UniversityFrankfurtamMain UniversityofBielefeld DepartmentofComputerScience Bielefeld andMathematics Germany FrankfurtamMain Germany SvenBanisch MaxPlanckInstituteforMathematics intheSciences Inselstrasse22 D-04103Leipzig Germany ISSN1860-0832 ISSN1860-0840 (electronic) UnderstandingComplexSystems ISBN978-3-662-47237-8 ISBN978-3-662-47238-5 (eBook) DOI10.1007/978-3-662-47238-5 LibraryofCongressControlNumber:2015940024 SpringerHeidelbergNewYorkDordrechtLondon (cid:2)c Springer-VerlagBerlinHeidelberg2016 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,theauthorsandtheeditorsaresafetoassumethattheadviceandinformationinthisbook arebelievedtobetrueandaccurateatthedateofpublication.Neitherthepublishernortheauthorsor theeditorsgiveawarranty,expressorimplied,withrespecttothematerialcontainedhereinorforany errorsoromissionsthatmayhavebeenmade. Printedonacid-freepaper Springer-VerlagGmbHBerlinHeidelbergispartofSpringerScience+BusinessMedia (www.springer.com) Introduction AlexanderMehler,AndyLu¨cking,SvenBanisch, PhilippeBlanchard,andBarbaraFrank-Job 1 Onthe Content ofThis Book Currently,weobserveanadventofapproachestoanalyzinglinguisticnetworkswith themethodsofstochasticphysicsandgraphtheory.Generallyspeaking,alinguis- tic network is represented by a graph whose vertices denote linguistic units (e.g., words, sentences, or textual units) and whose edges modellinguistic (e.g. syntac- tic,semanticorpragmatic)relationsoftheseunits.Theaimofmodelsoperatingon such networks is to capture the synchronic, topologicalor evolutionary dynamics oflinguisticsystems, say,onthephonological,morphological,syntactic,semantic orpragmaticlevel.Whatthese approacheshaveincommonisthattheymodelthe structuralor temporaldynamicsof linguistic systems in orderto test information- theoreticalorlinguistichypothesesonthegroundsofcomplexnetworktheory.This ispartlydoneintermsofastrongnetworkperspectiveaccordingtowhichthenet- workapproachisseentobeindispensabletotestthefocalhypotheses.Apparently, the area of language evolution provides a good test case for such an approach. AlexanderMehler·AndyLu¨cking Goethe-UniversityFrankfurtamMain,DepartmentofComputerScienceandMathematics, FrankfurtamMain,Germany e-mail:{Mehler,Luecking}@em.uni-frankfurt.de SvenBanisch MaxPlanckInstituteforMathematicsintheSciences,Inselstrasse22, D-04103Leipzig,Germany e-mail:[email protected] PhilippeBlanchard FacultyofPhysics,BielefeldUniversity,Germany e-mail:[email protected] BarbaraFrank-Job FacultyofLinguistics&LiteraryStudies,UniversityofBielefeld,Bielefeld,Germany e-mail:[email protected] VI A.Mehleretal. Language evolution can be seen as a meso system that connects language as a macro system with the micro system of cognitive processes of language process- ing.Startingfromsuch a unifiedapproachto languagestructure,languagechange andprocessing,networkapproachestry to gaininsightsinto the lawsof linguistic informationprocessingincommunitiesofsocialagents. Inspiteoftheremarkablesuccessregardingthedevelopmentofexpressivegraph modelsoflinguisticsystems,theseapproachesarestillinneedofaunifyingframe- work.Todate,themodelsareconnectedbyacommonmethodicalstancebasedon complexnetworktheoryinadditiontoquantitativelinguistics.Thus,wefacearange of diverse network models that focus on laws of information processing without clarifyingtheirsynergeticinterdependencies.Thisispartlyduetothelackofshared standardsofdatamodeling,oftheinteroperabilityofalgorithmicgraphmodelsand ofthesustainabilityoftheunderlyinglinguisticresourcesandcorpora.Obviously, interdisciplinary research across the boarder of computer science, linguistics and stochasticphysicsmayprofitfromtheavailabilityofsuchstandards. This book aims at making first steps into the direction of filling this gap. It presentstheoreticaland empiricalresultsin supportofa unifyingapproachto lin- guistic networks that may help to overcome bottleneck problems of this field of research.Tothisend,thebookcomprisesrecentresearcheffortsintheareaoflin- guisticnetworks.Itbringstogetherscientistswithdiversebackgroundsrangingfrom linguisticstotext-technology,fromcomputationalhumanitiestostatisticalnetwork theory.The bookis organized,roughly,into six partsincludingsemanticand syn- tactic networks, the interplay of language and cognition, the simulation of socio- linguisticdynamicsandtext-technologicalresourcesofnetworkmodeling.Special emphasisis putoncritical articlesand articlesthat reviewrecentdevelopmentsin thefield.Thisincludesthefollowingfieldsofresearch: (cid:129) Resourcesoflinguisticnetworkanalysis. (cid:129) Principlesoflinguisticnetworkinduction. (cid:129) Topologicalmodelsoflanguagestructure. (cid:129) Modelsoflanguagedynamics:evolution,diachrony,change. (cid:129) Unifiedmodelsfromstochasticphysics. (cid:129) Networkmodelsfromcognitivelinguistics. (cid:129) Networkmodelsofphonological,lexical,syntactic,semanticorpragmaticsys- tems. (cid:129) Networkmodelsoftextsystemsincontrasttolanguagesystems. Dealingwiththeseandrelatedtopics,theaimofthebookistoadvocateandpromote networkmodelsoflinguisticsystemsthatarebothbasedonthoroughmathematical modelsandsubstantiatedintermsoflinguisticinterpretations.Inthisway,thebook contributesfirststepstowardsestablishingastatisticalnetworktheoryasatheoret- ical basis of linguistic network analysis across the boarderof the naturalsciences andthehumanities. Introduction VII 2 Overview oftheBook 2.1 PartI:Cognition Successfulapplicationsofnetworkanalysiswithaparticularfocusontheinterplay of language and cognition are reviewed in the chapter of Beckage and Colunga. Concentratingonsemanticandphonologicalnetworks,itexploresnetworkfeatures andtheirrelationtohumanlanguageperformanceincludingtheapplicationtocog- nitiveimpairmentandatypicalbehavior. The chapter by Vitevitch, Goldstein and Johnson combines network tools and datafromapsycholinguisticexperimenttoexplorespeechperceptionerrorswiththe aimtounderstandbetterwhatisperceivedwhenaspokenwordismisperceived.The experimentalresultsoftheirphonologicalassociationtaskareevaluatedintermsof path’onanetworkofphonologicalsimilarity. The chapter by De Deyne, Verheyen and Storms compares semantic networks derivedfromtextcorporawithnetworksobtainedthroughwordassociationexper- iments by looking at macro- and mesoscopic properties of both types of graphs. Whiletheanalysisrevealsstructuralsimilaritiesatthegloballevel,significantdif- ferencesbetweentextandwordassociationgraphsemergeatalowerlevelofcom- munitystructureorcentrality.Thechapteralsopresentsacomparisonwithhuman relatednessjudgments. 2.2 PartII:Topology The chapter by Biemann, Krumov, Roos and Weihe presents a statistical analysis ofthemotifsignaturesofco-occurrencegraphsincludingco-authorshipnetworks, communication networks and linguistic co-occurrence graphs of natural and arti- ficial languages. Based on the hypothesis that different word classes serve differ- entfunctionsinalanguageananalysisofco-occurrencegraphsfordifferentword classes(verbsvs.nounsvs.adjectivesetc.)isperformedwhichshowsthatespecially verbsaredistinguishablefromotherwordclassesbytheirmotifsignature–across differentlanguages. ThechapterbyArau´joandBanischhighlightstheneedtoconsiderdifferentways ofnetworkinductioninnetwork-basedanalysisoflanguageandreasonsthatinduc- tionandanalysisarestronglyinterdependenttasks.Basedonaframeworkcompris- ing differentabstractionlevelsalongwith levelsof statistical analysis,the authors arguethatthefieldoflinguisticnetworksischallengedbythefactthataninterpre- tation of topological indicators used in network analysis becomes the harder, the highertheabstractionlevelofthenetwork. The chapter by Masucci, Kalampokis, Egu´ıluz and Herna´ndez-Garc´ıa presents an information-theoretic approach to derive a directed network of semantic flow between Wikipedia articles using a complete snapshot of the English Wikipedia. Theauthorsshowthattheresultingsemanticspaceischaracterizedbyascale-free behavior at differentscales which implies a hierarchicalorganization of semantic spaces. VIII A.Mehleretal. The chapter by Zweig confronts the physically-inspired context-free quest for universal structures with the need of contextual interpretations in sociology and in linguistics. Zweigquestionsthe usefulnessof networkrepresentationsofword- adjacencyrelations,becausemostofthewell-knowntopologicalindicatorsrelyona ratherspecificnetworkprocessandtheymaythereforebemisleadingifthisprocess isnotknownornotadequatelymodeledbytheprocessunderlyingthemethod. 2.3 PartIII:Syntax ThechapterbyCˇech,MacˇutekandLiupresentsacriticalreviewoftheapplication of complex network tools to the analysis of syntax and points out the main chal- lengesforfurtherresearch.Amongmanyotherthings,thearticlediscussestheim- pactofsyntaxonnetworkproperties,thepreprocessingofdata,andtheapplication ofnetworkstudiestolanguagetypologyandacquisition. A second chapter dealing with syntactic dependency networks is by Chen and Liu.Basedontwosyntacticdependencynetworksfromdifferentgenresthischapter analyses the syntactic status of three function words in Chinese. The importance (the authors propose the notion of syntactic centrality) of the words is analyzed byindependentlyremovingthemfromthe networkandcomparingtheirstatistical characteristicsbeforeandafterremoval. ThechapterbyFerreriCanchochallengestheexistingtheoryofsyntaxbycon- fronting the observation that syntactic dependencies between the words of a sen- tence rarely cross when drawn over a sentence with two null hypotheses for the expected number of crossings by chance. Relying on the trade-off between parsi- monyandexplanatorypower,thechapterarguesthattheminimizationofsyntactic dependencylength(asaprinciplethatderivesfromlimitedcomputationalresources ofthebrain)canexplainuncrossingdependenciesandthatthisexplanationis,from aneconomicpointofview,preferableoverexplanationsrelyingongrammar. 2.4 PartIV:Dynamics Theroleofculturaltransmissioninlanguagechangeacrossthreegenerationsisan- alyzed on the basis of an extended simulation model by Gong and Shuai. While transmissionwithintheoffspringgenerationandbetweentheoffspringandthepar- entgenerationfosterslanguagechangeand leads, at the same time, to mutualun- derstandability within generations and across consecutive generations, interaction betweenchildrenandtheirgrandparent’sgenerationplaysanimportantroleinpre- servingmutualcross-generationalunderstandabilityinthelongrun. AnothersimulationstudyispresentedbyBaxterwhocomplementshisnumerical resultswithanalyticalarguments.Drawingonanevolutionaryapproachtolanguage change,theauthorlooksindetailtotheconvergencebehaviorofthemodelondif- ferent social networks and with heterogeneous patterns of mutual influence that, takentogether,mayencodeavarietyofsocialstructures. Introduction IX The chapter by Maity and Mukherjee presents a simulation study of the effect ofinflexibleindividualsonthedynamicsofthenaminggameandshowsthatrigid minoritieslead to the emergenceof dominantstates in the population.The model isanalyzedonaseriesofstaticnetworksofdifferentcomplexityrangingfromthe completegraphtoscale-freetopologiesandadynamicnetworkobtainedfromreal- worldtime-varyingface-to-faceinteractiondataisalsoconsidered. 2.5 PartV:Resources Therequirementsofadataformatapplicabletothewiderangeoflinguisticnetwork dataarediscussedinthechapterbyStu¨hrenberg,DiewaldandGleim.Theauthors analyzevariousexistinggraphformatsinrelationtotheirexpressivityandsupport bycommontoolsfornetworkanalysisandproposeanextensionofGraphMLasa possiblycomplexdatamodelofa graphwhichallowstoquicklyextractviewsfor specifictasks,ratherthanextractingincoherentdifferentviewsfromrawdata.Itis noteworthy,thatthischaptergrewoutofaworkinggroupthatwasconstitutedatthe MLNconference. ThebookconcludeswiththechapterbyMehlerandGleimwhopresenttheLN system, an online platform for the automatic generation of lexical networks from texts.Itaddressestwocommunities:ontheonehandhumanitiesscholars(e.g.,his- toricalsemanticists)whoaimatstudyingthechangeoflanguageuseasanindicator of social-semantic change. On the other hand, network theorists who are in need ofnullmodelsformakinglinguisticnetworkscomparable.TheworkflowoftheLN system–usingGraphMLasanoutputstandardforlinguisticnetworks–isexplained andexemplified.
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