TY - GEN
T1 - One size does not fit all
T2 - 27th ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2019
AU - Yanovsky, Stav
AU - Hoernle, Nicholas
AU - Lev, Omer
AU - Gal, Kobi
N1 - Publisher Copyright:
© 2019 Association for Computing Machinery.
PY - 2019/6/7
Y1 - 2019/6/7
N2 - Badges are endemic to online interaction sites, from Question and Answer (Q&A) websites to ride sharing, as systems for rewarding participants for their contributions. This paper studies how badge design affects people's contributions and behavior over time. Past work has shown that badges "steer" people's behavior toward substantially increasing the amount of contributions before obtaining the badge, and immediately decreasing their contributions thereafter, returning to their baseline contribution levels. In contrast, we find that the steering effect depends on the type of user, as modeled by the rate and intensity of the user's contributions. We use these measures to distinguish between different groups of user activity, including users who are not affected by the badge system despite being significant contributors to the site. We provide a predictive model of how users change their activity group over the course of their lifetime in the system. We demonstrate our approach empirically in three different Q&A sites on Stack Exchange with hundreds of thousands of users, and we discuss the implications for system designers.
AB - Badges are endemic to online interaction sites, from Question and Answer (Q&A) websites to ride sharing, as systems for rewarding participants for their contributions. This paper studies how badge design affects people's contributions and behavior over time. Past work has shown that badges "steer" people's behavior toward substantially increasing the amount of contributions before obtaining the badge, and immediately decreasing their contributions thereafter, returning to their baseline contribution levels. In contrast, we find that the steering effect depends on the type of user, as modeled by the rate and intensity of the user's contributions. We use these measures to distinguish between different groups of user activity, including users who are not affected by the badge system despite being significant contributors to the site. We provide a predictive model of how users change their activity group over the course of their lifetime in the system. We demonstrate our approach empirically in three different Q&A sites on Stack Exchange with hundreds of thousands of users, and we discuss the implications for system designers.
UR - http://www.scopus.com/inward/record.url?scp=85068071300&partnerID=8YFLogxK
U2 - 10.1145/3320435.3320438
DO - 10.1145/3320435.3320438
M3 - Conference contribution
AN - SCOPUS:85068071300
T3 - ACM UMAP 2019 - Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization
SP - 113
EP - 120
BT - ACM UMAP 2019 - Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization
PB - Association for Computing Machinery, Inc
Y2 - 9 June 2019 through 12 June 2019
ER -