TY - JOUR
T1 - The Influence of Personality Traits on User Interaction with Recommendation Interfaces
AU - Yan, Dongning
AU - Chen, Li
N1 - Funding Information:
This research work was supported by the Hong Kong Research Grants Council (under project RGC/HKBU 12201620) and the Fundamental Research Funds of Shandong University, China.
Publisher Copyright:
© 2023 Association for Computing Machinery.
PY - 2023/3/10
Y1 - 2023/3/10
N2 - Users' personality traits can take an active role in affecting their behavior when they interact with a computer interface. However, in the area of recommender systems (RS), though personality-based RS has been extensively studied, most works focus on algorithm design, with little attention paid to studying whether and how the personality may influence users' interaction with the recommendation interface. In this manuscript, we report the results of a user study (with 108 participants) that not only measured the influence of users' personality traits on their perception and performance when using the recommendation interface but also employed an eye-tracker to in-depth reveal how personality may influence users' eye-movement behavior. Moreover, being different from related work that has mainly been conducted in a single product domain, our user study was performed in three typical application domains (i.e., electronics like smartphones, entertainment like movies, and tourism like hotels). Our results show that mainly three personality traits, i.e., Openness to experience, Conscientiousness, and Agreeableness, significantly influence users' perception and eye-movement behavior, but the exact influences vary across the domains. Finally, we provide a set of guidelines that might be constructive for designing a more effective recommendation interface based on user personality.
AB - Users' personality traits can take an active role in affecting their behavior when they interact with a computer interface. However, in the area of recommender systems (RS), though personality-based RS has been extensively studied, most works focus on algorithm design, with little attention paid to studying whether and how the personality may influence users' interaction with the recommendation interface. In this manuscript, we report the results of a user study (with 108 participants) that not only measured the influence of users' personality traits on their perception and performance when using the recommendation interface but also employed an eye-tracker to in-depth reveal how personality may influence users' eye-movement behavior. Moreover, being different from related work that has mainly been conducted in a single product domain, our user study was performed in three typical application domains (i.e., electronics like smartphones, entertainment like movies, and tourism like hotels). Our results show that mainly three personality traits, i.e., Openness to experience, Conscientiousness, and Agreeableness, significantly influence users' perception and eye-movement behavior, but the exact influences vary across the domains. Finally, we provide a set of guidelines that might be constructive for designing a more effective recommendation interface based on user personality.
KW - eye-tracking experiment
KW - Recommendation interface
KW - user personality
UR - http://www.scopus.com/inward/record.url?scp=85151887786&partnerID=8YFLogxK
U2 - 10.1145/3558772
DO - 10.1145/3558772
M3 - Journal article
AN - SCOPUS:85151887786
SN - 2160-6455
VL - 13
SP - 1
EP - 39
JO - ACM Transactions on Interactive Intelligent Systems
JF - ACM Transactions on Interactive Intelligent Systems
IS - 1
M1 - 3
ER -