Can e-Commerce Recommender Systems be More Popular with Online Shoppers if they are Mood-aware?

Fanjuan Shi, Jean-Luc Marini

2016

Abstract

This paper presents the result of a controlled experiment studying how mood state can affect the usage of e-commerce recommender system. The authors develop a mood recognition tool to classify online shoppers into stressed or relaxed mood state unobtrusively. By analyzing their reactions to recommended products when surfing on an e-commerce website, the authors make two conclusions. Firstly, stress negatively impacts the usage of recommender system. Secondly, relaxed users are more receptive to recommendations. These findings suggest that mood recognition tool can help recommender systems find the "right time" to intervene. And mood-aware recommender systems can enhance marketer-consumer interaction.

Paper Citation

in Harvard Style

Shi F. and Marini J. (2016). Can e-Commerce Recommender Systems be More Popular with Online Shoppers if they are Mood-aware? . In Proceedings of the 12th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST, ISBN 978-989-758-186-1, pages 173-180. DOI: 10.5220/0005618901730180

in Bibtex Style

@conference{webist16,
author={Fanjuan Shi and Jean-Luc Marini},
title={Can e-Commerce Recommender Systems be More Popular with Online Shoppers if they are Mood-aware?},
booktitle={Proceedings of the 12th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST,},
year={2016},
pages={173-180},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005618901730180},
isbn={978-989-758-186-1},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST,
TI - Can e-Commerce Recommender Systems be More Popular with Online Shoppers if they are Mood-aware?
SN - 978-989-758-186-1
AU - Shi F.
AU - Marini J.
PY - 2016
SP - 173
EP - 180
DO - 10.5220/0005618901730180