The Application of Affective Measures in Text-Based Emotion Aware Recommender Systems

John Leung, Igor Griva, William Kennedy, Jason Kinser, Sohyun Park, Seo Lee

2023

Abstract

This paper presents an innovative approach to address the problems researchers face in Emotion Aware Recommender Systems (EARS): the difficulty and cumbersome collecting voluminously good quality emotion-tagged datasets and an effective way to protect users’ emotional data privacy. Without enough goodquality emotion-tagged datasets, researchers cannot conduct repeatable affective computing research in EARS that generates personalized recommendations based on users’ emotional preferences. Similarly, if we fail to protect users’ emotional data privacy fully, users could resist engaging with EARS services. This paper introduced a method that detects affective features in subjective passages using the Generative Pre-trained Transformer Technology, forming the basis of the affective index and Affective Index Indicator (AII). Eliminate the need for users to build an affective feature detection mechanism. The paper advocates for a Separation of Responsibility approach where users protect their emotional profile data while EARS service providers refrain from retaining or storing it. Service providers can update users’ affective indices in memory without saving their privacy data, providing affective-aware recommendations without compromising user privacy. This paper offers a solution to the subjectivity and variability of emotions, data privacy concerns, and evaluation metrics and benchmarks, paving the way for future EARS research.

Paper Citation

in Harvard Style

Leung J., Griva I., Kennedy W., Kinser J., Park S. and Lee S. (2023). The Application of Affective Measures in Text-Based Emotion Aware Recommender Systems. In Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA; ISBN 978-989-758-664-4, SciTePress, pages 590-597. DOI: 10.5220/0012143900003541

in Bibtex Style

@conference{data23,
author={John Leung and Igor Griva and William Kennedy and Jason Kinser and Sohyun Park and Seo Lee},
title={The Application of Affective Measures in Text-Based Emotion Aware Recommender Systems},
booktitle={Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA},
year={2023},
pages={590-597},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012143900003541},
isbn={978-989-758-664-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA
TI - The Application of Affective Measures in Text-Based Emotion Aware Recommender Systems
SN - 978-989-758-664-4
AU - Leung J.
AU - Griva I.
AU - Kennedy W.
AU - Kinser J.
AU - Park S.
AU - Lee S.
PY - 2023
SP - 590
EP - 597
DO - 10.5220/0012143900003541
PB - SciTePress