Abundance of user contributions does not necessarily indicate sustainability of an online community. On the contrary, excessive contributions in the systems may result in information overload and user withdrawal. We propose a user- and community- adaptive reward mechanism aiming to regulate the quantity of the contributions and encourage users to moderate the quality of contributions themselves. The mechanism has been applied and evaluated in an online undergraduate students to share course-related web-resources.

This research presented in the paper is based upon research from authors' previous publication, User Motivation and Persuasion Strategy for Peer-to-peer Communities. It introduces a community model, individual model, adaptive rewards mechanism and other motivational concepts to increase user participation, the quality of user generated content and to influence user behavior (i.e. a personalised messages may be directed to a user for them to reduce the amount of articles they review but attempt to increase the quality of their reviews to gain a higher contribution level). It also discusses the concept of information overload, which occurs in an online community when users feel they are swamped with unwanted information.

Interestingly, the researchers have introduced a virtual currency in their case study application, Comtella, which they have called, c-points (points award for user contributions). More points are rewarded to people that provide more valuable contributions (defined from a combination of quantity and quality measures) and the points are then spent to increase the ranking position of their postings on search result pages. This increases the chance for the user to have their posts read and rated by other users. In depth analysis has also been conducted on quantifying contributions for specific parameters. For example, contribution posts allocated to users are higher when a new topic discussion begins and decreases gradually over time. This is a concept that I will review for the development of a generic user contribution measurement model for online communities. The models and ideas proposed in this research can be strengthened by testing them with different types of online communities (i.e. not just a online learning community).

• Critical mass
• Sustainable user participation
• Information overload
• Social comparison
• Reputation
• Subjectiveness in evaluating content quality