Harvesting Context and Mining Emotions Related to Olfactory Cultural Heritage

M.Besher Massri; Inna Novalija; Dunja Mladenić; Janez Brank; Sara Graça Da Silva; Natasza Marrouch; Carla Murteira; Ali Hürriyetoğlu; Beno Šircelj

doi:10.20944/preprints202206.0050.v1

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preprints.org > computer science and mathematics > artificial intelligence and machine learning > doi: 10.20944/preprints202206.0050.v1

Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Harvesting Context and Mining Emotions Related to Olfactory Cultural Heritage

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Version 1 : Received: 1 June 2022 / Approved: 6 June 2022 / Online: 6 June 2022 (02:50:24 CEST)
Version 2 : Received: 1 August 2022 / Approved: 2 August 2022 / Online: 2 August 2022 (07:57:35 CEST)

A peer-reviewed article of this Preprint also exists.

Massri, M.B.; Novalija, I.; Mladenić, D.; Brank, J.; Graça da Silva, S.; Marrouch, N.; Murteira, C.; Hürriyetoğlu, A.; Šircelj, B. Harvesting Context and Mining Emotions Related to Olfactory Cultural Heritage. Multimodal Technol. Interact. 2022, 6, 57. Massri, M.B.; Novalija, I.; Mladenić, D.; Brank, J.; Graça da Silva, S.; Marrouch, N.; Murteira, C.; Hürriyetoğlu, A.; Šircelj, B. Harvesting Context and Mining Emotions Related to Olfactory Cultural Heritage. Multimodal Technol. Interact. 2022, 6, 57.

Abstract

This paper presents an Artificial Intelligence approach to mining context and emotions related to olfactory cultural heritage narratives, in particular to fairy tales. We provide an overview of the role of smell and emotions in literature, as well as highlight the importance of olfactory experience and emotions from psychology and linguistic perspectives. We introduce a methodology for extracting smells and emotions from text, as well as demonstrate the context-based visualizations related to smells and emotions implemented in a novel Smell Tracker tool. The evaluation is performed using a collection of fairy tales from Grimm and Andersen. We find out that fairy tales often connect smell with emotional charge of situations. The experimental results show that we can detect smells and emotions with F1 score of 92.7 and 79.2, respectively.

Keywords

Emotions Mining; Context Mining; Sensory Mining; Artificial Intelligence; Information extraction; Text classification; Fairy tales; Olfactory Cultural Heritage

Subject

Computer Science and Mathematics, Artificial Intelligence and Machine Learning

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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