To incentivize users' participations and steer their online activities, online social networks start to provide users with various kinds of rewards for their contributions to the sites. The most frequently distributed rewards include account levels, reputation scores, different kinds of badges, and even material awards like small gifts and cash back, etc. Attracted by these rewards, users will spend more time using the network services. In this paper, we will mainly focus on "badges reward systems" but the proposed models can be applied to other reward systems as well. Badges are small icons attached to users' homepages and profiles denoting their achievements. People like to accumulate badge for various reasons and different badges can have specific values for them. Meanwhile, to get badges, they also need to exert efforts to finish the required tasks, which can lead to certain costs. To understand and model users' motivations in badge achievement activities, we will study an existing badge system launched inside a real-world online social network, Foursquare, in this paper. At the same time, to maximize users' contributions to online social networks, social network system designers need to determine the optimal badge system mechanism carefully. Badge system mechanism describes various detailed aspects of the system and can involve many parameters, e.g., categories of existing badges, number of badges available as well as the minimum contributions required to obtain the badges, which all need to be designed with meticulous investigations. Based on the model of users' badges accumulating activities, in this paper, we will also study how to design the badge system that can incentivize the maximum users' contributions to the social networks.
To achieve the maximal contribution to the sites, many works have been done on designing the badge system for online social networks. Jain et. al. @cite_2 study the problem of incentive design for online question and answer sites. Anderson et. al. @cite_12 study how badges can influence and steer users behavior on social networks, which can lead both to increased participation and to changes in the mix of activities a user pursues in the network. Ghosh et. al. @cite_13 study the problem of implementing a mechanism which can lead to optimal outcomes in social computing based on a game-theoretic approach. Immorlica et. al. @cite_16 study the badge system design whose goal is to maximize contributions. Easley et. al. @cite_3 take a game-theoretic approach to badge design, analyzing the incentives created by badges and potential contributors as well as their contribution to the sites.
@cite_3 @cite_2 @cite_16 @cite_13 @cite_12
2025280459 2124810512 2951092054 2951605358 2148527862
Gamification is growing increasingly prevalent as a means to incentivize user engagement of social media sites that rely on user contributions. Badges, or equivalent rewards, such as top-contributor lists that are used to recognize a user's contributions on a site, clearly appear to be valued by users who actively pursue and compete for them. However, different sites use different badge designs, varying how, and for what, badges are awarded. Some sites, such as StackOverflow, award badges for meeting fixed levels of contribution. Other sites, such as Amazon and Y! Answers, reward users for being among some top set of contributors on the site, corresponding to a competitive standard of performance. Given that users value badges, and that contributing to a site requires effort, how badges are designed will affect the incentives—therefore the participation and effort—elicited from strategic users on a site. We take a game-theoretic approach to badge design, analyzing the incentives created by widely used badge designs in a model in which winning a badge is valued, effort is costly, and potential contributors to the site endogenously decide whether or not to participate, and how much total effort to put into their contributions to the site. We analyze equilibrium existence, as well as equilibrium participation and effort, in an absolute standards mechanism Mα in which badges are awarded for meeting some absolute level of (observed) effort, and a relative standards mechanism Mρ corresponding to competitive standards, as in a top-ρ contributor badge. We find that equilibria always exist in both mechanisms, even when the value from winning a badge depends endogenously on the number of other winners. However, Mα has zero-participation equilibria for standards that are too high, whereas all equilibria in Mρ elicit nonzero participation for all possible ρ, provided that ρ is specified as a fixed number rather than as a fraction of actual contributors (note that the two are not equivalent in a setting with endogenous participation). Finally, we ask whether or not a site should explicitly announce the number of users winning a badge. The answer to this question is determined by the curvature of the value of winning the badge as a function of the number of other winners. In this paper, we provide a simple game-theoretic model of an online question and answer forum. We focus on factual questions in which user responses aggregate while a question remains open. Each user has a unique piece of information and can decide when to report this information. The asker prefers to receive information sooner rather than later, and will stop the process when satisfied with the cumulative value of the posted information. We consider two distinct cases: a complements case, in which each successive piece of information is worth more to the asker than the previous one; and a substitutes case, in which each successive piece of information is worth less than the previous one. A best-answer scoring rule is adopted to model Yahoo! Answers, and is effective for substitutes information, where it isolates an equilibrium in which all users respond in the first round. But we find that this rule is ineffective for complements information, isolating instead an equilibrium in which all users respond in the final round. In addressing this, we demonstrate that an approval-voting scoring rule and a proportional-share scoring rule can enable the most efficient equilibrium with complements information, under certain conditions, by providing incentives for early responders as well as the user who submits the final answer. Many websites rely on user-generated content to provide value to consumers. These websites typically incentivize participation by awarding users badges based on their contributions. While these badges typically have no explicit value, they act as symbols of social status within a community. In this paper, we consider the design of badge mechanisms for the objective of maximizing the total contributions made to a website. Users exert costly effort to make contributions and, in return, are awarded with badges. A badge is only valued to the extent that it signals social status and thus badge valuations are determined endogenously by the number of users who earn each badge. The goal of this paper is to study the design of optimal and approximately badge mechanisms under these status valuations. We characterize badge mechanisms by whether they use a coarse partitioning scheme, i.e. awarding the same badge to many users, or use a fine partitioning scheme, i.e. awarding a unique badge to most users. We find that the optimal mechanism uses both fine partitioning and coarse partitioning. When status valuations exhibit a decreasing marginal value property, we prove that coarse partitioning is a necessary feature of any approximately optimal mechanism. Conversely, when status valuations exhibit an increasing marginal value property, we prove that fine partitioning is necessary for approximate optimality. In many social computing applications such as online Q&A forums, the best contribution for each task receives some high reward, while all remaining contributions receive an identical, lower reward irrespective of their actual qualities. Suppose a mechanism designer (site owner) wishes to optimize an objective that is some function of the number and qualities of received contributions. When potential contributors are strategic agents, who decide whether to contribute or not to selfishly maximize their own utilities, is such a "best contribution" mechanism, M_B, adequate to implement an outcome that is optimal for the mechanism designer? We first show that in settings where a contribution's value is determined primarily by an agent's expertise, and agents only strategically choose whether to contribute or not, contests can implement optimal outcomes: for any reasonable objective, the rewards for the best and remaining contributions in M_B can always be chosen so that the outcome in the unique symmetric equilibrium of M_B maximizes the mechanism designer's utility. We also show how the mechanism designer can learn these optimal rewards when she does not know the parameters of the agents' utilities, as might be the case in practice. We next consider settings where a contribution's value depends on both the contributor's expertise as well as her effort, and agents endogenously choose how much effort to exert in addition to deciding whether to contribute. Here, we show that optimal outcomes can never be implemented by contests if the system can rank the qualities of contributions perfectly. However, if there is noise in the contributions' rankings, then the mechanism designer can again induce agents to follow strategies that maximize his utility. Thus imperfect rankings can actually help achieve implementability of optimal outcomes when effort is endogenous and influences quality. An increasingly common feature of online communities and social media sites is a mechanism for rewarding user achievements based on a system of badges. Badges are given to users for particular contributions to a site, such as performing a certain number of actions of a given type. They have been employed in many domains, including news sites like the Huffington Post, educational sites like Khan Academy, and knowledge-creation sites like Wikipedia and Stack Overflow. At the most basic level, badges serve as a summary of a user's key accomplishments; however, experience with these sites also shows that users will put in non-trivial amounts of work to achieve particular badges, and as such, badges can act as powerful incentives. Thus far, however, the incentive structures created by badges have not been well understood, making it difficult to deploy badges with an eye toward the incentives they are likely to create. In this paper, we study how badges can influence and steer user behavior on a site---leading both to increased participation and to changes in the mix of activities a user pursues on the site. We introduce a formal model for reasoning about user behavior in the presence of badges, and in particular for analyzing the ways in which badges can steer users to change their behavior. To evaluate the main predictions of our model, we study the use of badges and their effects on the widely used Stack Overflow question-answering site, and find evidence that their badges steer behavior in ways closely consistent with the predictions of our model. Finally, we investigate the problem of how to optimally place badges in order to induce particular user behaviors. Several robust design principles emerge from our framework that could potentially aid in the design of incentives for a broad range of sites.