Data analysis and modeling pipelines for controlled networked social science experiments

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dc.contributor.authorCedeno-Mieles, Vanessaen
dc.contributor.authorHu, Zhihaoen
dc.contributor.authorRen, Yihuien
dc.contributor.authorDeng, Xinweien
dc.contributor.authorContractor, Noshiren
dc.contributor.authorEkanayake, Saliyaen
dc.contributor.authorEpstein, Joshua M.en
dc.contributor.authorGoode, Brian J.en
dc.contributor.authorKorkmaz, Gizemen
dc.contributor.authorKuhlman, Christopher J.en
dc.contributor.authorMachi, Dustinen
dc.contributor.authorMacy, Michaelen
dc.contributor.authorMarathe, Madhav V.en
dc.contributor.authorRamakrishnan, Narenen
dc.contributor.authorSaraf, Parangen
dc.contributor.authorSelf, Nathanen
dc.date.accessioned2021-10-04T14:47:26Zen
dc.date.available2021-10-04T14:47:26Zen
dc.date.issued2020-11-24en
dc.date.updated2021-10-04T14:47:09Zen
dc.description.abstractThere is large interest in networked social science experiments for understanding human behavior at-scale. Significant effort is required to perform data analytics on experimental outputs and for computational modeling of custom experiments. Moreover, experiments and modeling are often performed in a cycle, enabling iterative experimental refinement and data modeling to uncover interesting insights and to generate/refute hypotheses about social behaviors. The current practice for social analysts is to develop tailor-made computer programs and analytical scripts for experiments and modeling. This often leads to inefficiencies and duplication of effort. In this work, we propose a pipeline framework to take a significant step towards overcoming these challenges. Our contribution is to describe the design and implementation of a software system to automate many of the steps involved in analyzing social science experimental data, building models to capture the behavior of human subjects, and providing data to test hypotheses. The proposed pipeline framework consists of formal models, formal algorithms, and theoretical models as the basis for the design and implementation. We propose a formal data model, such that if an experiment can be described in terms of this model, then our pipeline software can be used to analyze data efficiently. The merits of the proposed pipeline framework is elaborated by several case studies of networked social science experiments.en
dc.description.versionPublished versionen
dc.format.extent58 page(s)en
dc.format.mimetypeapplication/pdfen
dc.identifierARTN e0242453 (Article number)en
dc.identifier.doihttps://doi.org/10.1371/journal.pone.0242453en
dc.identifier.eissn1932-6203en
dc.identifier.issn1932-6203en
dc.identifier.issue11en
dc.identifier.orcidDeng, Xinwei [0000-0002-1560-2405]en
dc.identifier.otherPONE-D-20-13649 (PII)en
dc.identifier.pmid33232347en
dc.identifier.urihttp://hdl.handle.net/10919/105155en
dc.identifier.volume15en
dc.language.isoenen
dc.publisherPLOSen
dc.relation.urihttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000595863100009&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=930d57c9ac61a043676db62af60056c1en
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectWORKFLOW MANAGEMENTen
dc.subjectCOLLECTIVE IDENTITYen
dc.subjectINITIAL CONFIDENCEen
dc.subjectONLINEen
dc.subjectATTRIBUTIONen
dc.subjectDESIGNen
dc.subjectRESPONSIBILITYen
dc.subjectFAILUREen
dc.subjectVALENCEen
dc.subjectSUCCESSen
dc.subject.meshHumansen
dc.subject.meshSocial Behavioren
dc.subject.meshSocial Sciencesen
dc.subject.meshAlgorithmsen
dc.subject.meshModels, Theoreticalen
dc.subject.meshSoftwareen
dc.subject.meshElectronic Data Processingen
dc.titleData analysis and modeling pipelines for controlled networked social science experimentsen
dc.title.serialPLOS ONEen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.otherArticleen
dc.type.otherJournalen
dcterms.dateAccepted2020-11-03en
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/Scienceen
pubs.organisational-group/Virginia Tech/Science/Statisticsen
pubs.organisational-group/Virginia Tech/Engineeringen
pubs.organisational-group/Virginia Tech/Engineering/Computer Scienceen
pubs.organisational-group/Virginia Tech/All T&R Facultyen
pubs.organisational-group/Virginia Tech/Engineering/COE T&R Facultyen
pubs.organisational-group/Virginia Tech/Science/COS T&R Facultyen

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