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Artificial Intelligence identifying patterns in the social interaction of senior individuals through online activities at Virtual Senior University in Pandemic

dc.contributor.authorDOMINGUES, A. M.
dc.date.accessioned2024-01-29T15:24:07Z
dc.date.available2024-01-29T15:24:07Z
dc.date.issued2023-07-14
dc.description.abstractObjectives: Data Mining techniques applied to observe patterns in the social interaction of senior individuals during their participation in the online activities that were proposed by the Virtual Senior University during the pandemic. Methodology: Zoom and Facebook platforms were used to streamline conversations, videos with student performances and homework during the COVID-19 pandemic. The experiments conducted enabled the application of the Artificial Intelligence technique called Data Mining to perform statistical analyses and identify profiles based on the social interaction of the individuals who participated in the online activities. Participants answered about Gender, Age (years), Marital Status, Time attending Senior University and Participation in online activities. They also answered about their participation in these activities, informing if it increased, decreased, remained unchanged or if they did not participate. To carry out the analyses of the collected data, age groups were organized, being 50 to 64 years, 65 to 74 years and 75 or more years. Results and Discussion: It was observed that the majority of seniors who had been attending the Virtual Senior University since before 2020, aged between 50 and 64 years, reported that their participation in online activities had increased. According to the analysis that was carried out, it was possible to correctly classify 76.087% of the data. The accuracy described through the Kappa statistic coefficient showed reliability in the data showing a score of 0.6383 and corresponding to a substantial agreement (range between 0.61 and 0.80). Conclusions: The Data Mining technique applied in this study suggests that there was statistical significance for the analyses carried out based on the social interaction of senior individuals, in the age group between 50 and 64 years old, who participated in the online activities proposed by the Virtual Senior University during the pandemic. Different activities are suggested for the other age groups.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.urihttp://hdl.handle.net/10400.26/49427
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.subjectArtificial Intelligencept_PT
dc.subjectSocial Interactionpt_PT
dc.subjectVirtual Senior Universitypt_PT
dc.subjectPandemicpt_PT
dc.titleArtificial Intelligence identifying patterns in the social interaction of senior individuals through online activities at Virtual Senior University in Pandemicpt_PT
dc.typereview
dspace.entity.typePublication
oaire.citation.title3º CONGRESSO INTERNACIONAL AGE.COMM SUSTENTABILIDADE E ENVELHECIMENTOpt_PT
person.familyNameDomingues
person.givenNameAndréia Miranda
person.identifier.ciencia-idB611-685E-7C05
rcaap.rightsopenAccesspt_PT
rcaap.typereviewpt_PT
relation.isAuthorOfPublication366362c8-db36-4d8f-91b4-37472af78f5d
relation.isAuthorOfPublication.latestForDiscovery366362c8-db36-4d8f-91b4-37472af78f5d

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