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Authors: Fanjuan Shi 1 and Jean-Luc Marini 2

Affiliations: 1 Shanghai Unicore Technology of IOT Co., LTD and Search’XPR SAS, China ; 2 Search’XPR SAS, France

ISBN: 978-989-758-186-1

Keyword(s): Mood Recognition, e-Commerce Recommender System, Behavioral Data Mining, User-centric Systems.

Related Ontology Subjects/Areas/Topics: B2B, B2C and C2C ; Communication and Software Technologies and Architectures ; e-Business ; Enterprise Information Systems ; Recommendation Systems ; Society, e-Business and e-Government ; Software Agents and Internet Computing ; Web Information Systems and Technologies

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.

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Paper citation in several formats:
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

@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},
}

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

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