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Social Web Analysis for Decision Support: A Case Study

2023Book part Open access
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dc.contributor.authorFreire, Manuela
dc.contributor.authorAntunes, Francisco
dc.contributor.authorCosta, João Paulo
dc.date.accessioned2024-01-11T12:14:33Z
dc.date.available2024-01-11T12:14:33Z
dc.date.issued2023
dc.description.abstractIn this study, we focused on analyzing customer-generated data on Facebook to explore how textual content on a social web can provide valuable information for decision support. To accomplish this goal, we used several techniques that included social network analysis (SNA), natural language processing (NLP), data mining (DM), and machine learning (ML), integrating them with artificial intelligence approaches. Our analysis aimed to harness the information generated during the Volkswagen pollutant emissions situation in a case study that was conducted using the textual content from 10,642 posts, that represented the interactions of 25,877 users over a span of twenty-two weeks. The results demonstrated that monitoring online social networks (OSNs) can significantly enhance decision-making processes and might help to mitigate potential damages to brands/businesses. By leveraging the proposed methodological approach, a set of orientations for decision-making was extracted, providing valuable guidance for brand management and reputation protection. Overall, this study highlights the importance of analyzing textual content on OSNs and leveraging advanced computational techniques to improve decision support.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.3233/FAIA230770pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.6/13956
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherIOS Presspt_PT
dc.relationInstitute for Systems Engineering and Computers at Coimbra - INESC Coimbra
dc.relationCentre for Business and Economics Research - University of Coimbra
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/pt_PT
dc.subjectSocial network analysispt_PT
dc.subjectNatural language processingpt_PT
dc.subjectData miningpt_PT
dc.subjectDecision supportpt_PT
dc.subjectMachine learningpt_PT
dc.subjectArtificial intelligencept_PT
dc.titleSocial Web Analysis for Decision Support: A Case Studypt_PT
dc.typebook part
dspace.entity.typePublication
oaire.awardTitleInstitute for Systems Engineering and Computers at Coimbra - INESC Coimbra
oaire.awardTitleCentre for Business and Economics Research - University of Coimbra
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00308%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05037%2F2020/PT
oaire.citation.conferencePlaceJ.-L. Kim (Ed.)pt_PT
oaire.citation.endPage98pt_PT
oaire.citation.startPage89pt_PT
oaire.citation.titleFrontiers in Artificial Intelligence and Applicationspt_PT
oaire.citation.volumeVolume 374: Machine Learning and Artificial Intelligencept_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
person.familyNameSousa Freire
person.familyNameAntunes
person.familyNameCosta
person.givenNameMª Manuela
person.givenNameFrancisco
person.givenNameJoão
person.identifier6ojfdQ4AAAAJ
person.identifier.ciencia-id181D-0501-8B0F
person.identifier.ciencia-idAE15-3381-6C2A
person.identifier.ciencia-id0312-CF54-C583
person.identifier.orcid0000-0002-5607-555X
person.identifier.orcid0000-0002-3569-7480
person.identifier.orcid0000-0001-5204-3916
person.identifier.ridN-2504-2013
person.identifier.ridM-5560-2013
person.identifier.scopus-author-id56286030200
person.identifier.scopus-author-id35992337000
person.identifier.scopus-author-id7402460396
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typebookPartpt_PT
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