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dc.contributor.authorCasales-Garcia, Vicente
dc.contributor.authorFalomir, Zoe
dc.contributor.authorMuseros, Lledó
dc.contributor.authorSanz, Ismael
dc.contributor.authorLlidó Escrivá, Dolores María
dc.contributor.authorGonzález Abril, L.
dc.date.accessioned2023-03-21T08:52:26Z
dc.date.available2023-03-21T08:52:26Z
dc.date.issued2022
dc.identifier.citationCASALES GARCÍA, V. et al. Analysing Food-Porn Images for Users’ Engagement in the Food Business. En Artificial Intelligence Research and Development A. Cortés et al. (Eds.). IOS Press, 2022. p. 67-70.ca_CA
dc.identifier.issn9781643683263
dc.identifier.issn9781643683270
dc.identifier.urihttp://hdl.handle.net/10234/202000
dc.descriptionPonència presentada a 24th International Conference of the Catalan Association for Artificial Intelligence, celebrada a Barcelona en 2022.ca_CA
dc.description.abstractThis paper presents an approach for analysing food-porn images and their related comments published by the cooking school Getcookingcanada Instagram account. Our approach processes the published images to extract colour parameters, counts the number of likes, and also analyses the comments related to each publication. A dataset containing all these was built, and methods were applied to study correlations among the data: a regression analysis, an ANOVA and a sentiment analysis of the comments on the dataset to explain the relation between the quantity of likes and the sentiment obtained from the food images. Our results show a correlation between the number of likes and the sentiment analysis of the comments. Images that evoke a positive sentiment have a higher number of likes and comments. Users’ experience on creating posts is also analysed and confirms a positive correlation between the number of likes and the publisher’s experience.ca_CA
dc.format.extent4 p.ca_CA
dc.format.mimetypeapplication/pdfca_CA
dc.language.isoengca_CA
dc.publisherIOS Pressca_CA
dc.relation.isPartOfFrontiers in Artificial Intelligence and Applications, Vol. 356, 2022.ca_CA
dc.rights© 2022 The authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0). doi:10.3233/FAIA220316ca_CA
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/ca_CA
dc.subjectSentimental analysisca_CA
dc.subjectFood-pornca_CA
dc.subjectregressionca_CA
dc.subjectAnovaca_CA
dc.subjectdeep learningca_CA
dc.titleAnalysing Food-Porn Images for Users’ Engagement in the Food Businessca_CA
dc.typeinfo:eu-repo/semantics/conferenceObjectca_CA
dc.identifier.doihttps://doi.org/10.3233/FAIA220316
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_CA
dc.relation.publisherVersionhttps://ebooks.iospress.nl/volumearticle/61222ca_CA
dc.type.versioninfo:eu-repo/semantics/publishedVersionca_CA
project.funder.nameAgencia Estatal de Investigaciónca_CA
project.funder.nameUniversitat Jaume Ica_CA
oaire.awardNumberFPU 17/00014ca_CA
oaire.awardNumberPDC2021-121097-I00ca_CA
oaire.awardNumberRYC2019-027177-I / AEI / 10.13039/501100011033ca_CA
oaire.awardNumberUJIB2020-15ca_CA
oaire.awardNumberPGC2018-102145-B-C21ca_CA


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© 2022 The authors and IOS Press.
This article is published online with Open Access by IOS Press and distributed under the terms
of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).
doi:10.3233/FAIA220316
Excepto si se señala otra cosa, la licencia del ítem se describe como: © 2022 The authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0). doi:10.3233/FAIA220316