One size does not fit all: A study of badge behavior in stack overflow

Stav Yanovsky, Nicholas Hoernle, Omer Lev and Kobi Gal

Journal of the Association for Information Science & Technology, 2021, vol. 72, issue 3, 331-345

Abstract: 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 article 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, for two types of activities (editing and voting on posts).

Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1002/asi.24409

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jinfst:v:72:y:2021:i:3:p:331-345

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=2330-1635

Access Statistics for this article

More articles in Journal of the Association for Information Science & Technology from Association for Information Science & Technology
Bibliographic data for series maintained by Wiley Content Delivery ().