Systematic Reciprocal Rewards: Motivating Expert Participation in Online Communities with a Novel Class of Incentives

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4 years 9 months
Full name
Ryan Anderson
Abstract
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Online communities such as question and answer (QA) systems are growing rapidly and we increasingly rely on them for valuable information and entertainment. However, finding meaningful rewards to motivate participation from the most qualified users, or experts, presents researchers with two main challenges: identifying these users and (2) rewarding their participation. Using an interdisciplinary theoretical framework, we illustrate possibilities for identifying and motivating the most valuable contributors to online communities. We suggest that access to peer-generated content can directly motivate people to apply their own expertise, thereby generating more content. Survey data from 380 participants suggests that users strongly prefer a novel class of incentives—reciprocal systemic rewards—to traditional achievement-based rewards. Overall, this research presents important considerations for many different types of online communities, including social networking and news aggregation sites.

CITATION:
DeAngelis, D. and K.S. Barber, “Systematic Reciprocal Rewards: Motivating Expert Participation in Online Communities with a Novel Class of Incentives,” International Journal of Agent Technologies and Systems (IJATS), Vol. 6(2), pp. 30-50, 2014

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Systematic Reciprocal Rewards: Motivating Expert Participation in Online Communities with a Novel Class of Incentives, D. DeAngelis, and K.Suzanne Barber, International Journal of Agent Technologies and Systems (IJATS), Vol. 6(2), pp. 30-50, 2014