It is important to enable peers to represent and update their trust in other peers in open networks for sharing files, and especially services. In this paper, we propose a Bayesian network-based trust model and a method for building reputation based on recommendations in peer-topeer networks. Since t rust is multi-faceted, peers need to develop differentiated trust in different aspects of other peers' capability. The peer's needs are different in different situations. Depending on the situation, a peer may need to consider its trust in a specific aspect of another peer's capability or in multiple aspects. Bayesian networks provide a flexible method to present differentiated trust and combine different aspects of trust. The evaluation of the model using a simulation shows that the system where peers communicate their experiences (recommendations) outperforms the system where peers do not share recommendations with each other and that a differentiated trust adds to the performance in terms of percentage of successful interactions.

No abstract

Abstract

The explosive growth of Web-based social applications over the last 10 years has led people to engage in online communities for various purposes: to work, learn, play, share time and mementos with friends and family and engage in public action. Social Computing Applications (SCA) allow users to discuss various topics in online forums, share their thoughts in blogs, share photos, videos, bookmarks, and connect with friends through social networks. Yet, the design of successful social applications that attract and sustain active contribution by their users still remains more of an art than a science. My research over the last 10 years has been based on the hypothesis that it is possible to incorporate mechanisms and tools in the design of the social application that can motivate users to participate, and more generally, to change their behavior in a desirable way, which is beneficial for the community. Since different people are motivated by different things, it can be expected that personalizing the incentives and the way the rewards are presented to the individual, would be beneficial. Also since communities have different needs in different phases of their existence, it is necessary to model the changing needs of communities and adapt the incentive mechanisms accordingly, to attract the kind of contributions that are beneficial. Therefore User and Group (Community) Modeling is an important area in the design of incentive mechanisms. This paper presents an overview of different approaches to motivate users to participate. These approaches are based on various theories from the area of social psychology and behavioral economics and involve rewards mechanisms, reputation, open group user modeling, and social visualization. Future trends are outlined towards convergence with the areas of persuasive systems design, adaptive/personalized systems, and intelligent social learning environments.

No abstract

Persuasive games are an effective approach for motivating health behavior, and recent years have seen an increase in games designed for changing human behaviors or attitudes. However, these games are limited in two major ways: first, they are not based on theories of what motivates healthy behavior change. This makes it difficult to evaluate why a persuasive approach works. Second, most persuasive games treat players as a monolithic group. As an attempt to resolve these weaknesses, we conducted a large-scale survey of 642 gamers' eating habits and their associated determinants of healthy behavior to understand how health behavior relates to gamer type. We developed seven different models of healthy eating behavior for the gamer types identified by BrainHex. We then explored the differences between the models and created two approaches for effective persuasive game design based on our results. The first is a one-sizefits-all approach that will motivate the majority of the population, while not demotivating any players. The second is a personalized approach that will best motivate a particular type of gamer. Finally, to make our approaches actionable in persuasive game design, we map common game mechanics to the determinants of healthy behavior.

The issues of trust fraud, product genuineness and price dispersion jointly make Chinese C2C buyers difficult to identify trustworthy sellers with a low price. Little is known about the generation of initial trust when buyers search products and receive lists of widely ranged prices. This study proposes a theoretical model to explain how price dispersion interacts with other factors in C2C purchase, such as initial trust, perceived risk, perceived value and purchase intention. Product type is considered as a moderator. 261 students were invited in a survey-based experiment. The results from PLS analysis show that price dispersion negatively affects perceived value, whilst, positively affects perceived risk, which further influences perceived value negatively. Price dispersion also negatively influences initial trust through perceived risk. Moreover, the negative effects of price dispersion are stronger when buyers purchase high-touch products.Keywords: consumer to consumer, trust, price dispersion, purchase intention, perceived risk The issues of trust fraud, product genuineness and price dispersion jointly make Chinese C2C buyers difficult to identify trustworthy sellers with a low price. Little is known about the generation of initial trust when buyers search products and receive lists of widely ranged prices. This study proposes a theoretical model to explain how price dispersion interacts with other factors in C2C purchase, such as initial trust, perceived risk, perceived value and purchase intention. Product type is considered as a moderator. 261 students were invited in a survey-based experiment. The results from PLS analysis show that price dispersion negatively affects perceived value, whilst, positively affects perceived risk, which further influences perceived value negatively. Price dispersion also negatively influences initial trust through perceived risk. Moreover, the negative effects of price dispersion are stronger when buyers purchase high-touch products.

No abstract