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Analysing Food-Porn Images for Users’ Engagement in the Food Business
dc.contributor.author | Casales-Garcia, Vicente | |
dc.contributor.author | Falomir, Zoe | |
dc.contributor.author | Museros, Lledó | |
dc.contributor.author | Sanz, Ismael | |
dc.contributor.author | Llidó Escrivá, Dolores María | |
dc.contributor.author | González Abril, L. | |
dc.date.accessioned | 2023-03-21T08:52:26Z | |
dc.date.available | 2023-03-21T08:52:26Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | CASALES 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.issn | 9781643683263 | |
dc.identifier.issn | 9781643683270 | |
dc.identifier.uri | http://hdl.handle.net/10234/202000 | |
dc.description | Ponència presentada a 24th International Conference of the Catalan Association for Artificial Intelligence, celebrada a Barcelona en 2022. | ca_CA |
dc.description.abstract | This 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.extent | 4 p. | ca_CA |
dc.format.mimetype | application/pdf | ca_CA |
dc.language.iso | eng | ca_CA |
dc.publisher | IOS Press | ca_CA |
dc.relation.isPartOf | Frontiers 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/FAIA220316 | ca_CA |
dc.rights.uri | http://creativecommons.org/licenses/by-nc/4.0/ | ca_CA |
dc.subject | Sentimental analysis | ca_CA |
dc.subject | Food-porn | ca_CA |
dc.subject | regression | ca_CA |
dc.subject | Anova | ca_CA |
dc.subject | deep learning | ca_CA |
dc.title | Analysing Food-Porn Images for Users’ Engagement in the Food Business | ca_CA |
dc.type | info:eu-repo/semantics/conferenceObject | ca_CA |
dc.identifier.doi | https://doi.org/10.3233/FAIA220316 | |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | ca_CA |
dc.relation.publisherVersion | https://ebooks.iospress.nl/volumearticle/61222 | ca_CA |
dc.type.version | info:eu-repo/semantics/publishedVersion | ca_CA |
project.funder.name | Agencia Estatal de Investigación | ca_CA |
project.funder.name | Universitat Jaume I | ca_CA |
oaire.awardNumber | FPU 17/00014 | ca_CA |
oaire.awardNumber | PDC2021-121097-I00 | ca_CA |
oaire.awardNumber | RYC2019-027177-I / AEI / 10.13039/501100011033 | ca_CA |
oaire.awardNumber | UJIB2020-15 | ca_CA |
oaire.awardNumber | PGC2018-102145-B-C21 | ca_CA |
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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