843 research outputs found

    Incentive Compatible Influence Maximization in Social Networks and Application to Viral Marketing

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    Information diffusion and influence maximization are important and extensively studied problems in social networks. Various models and algorithms have been proposed in the literature in the context of the influence maximization problem. A crucial assumption in all these studies is that the influence probabilities are known to the social planner. This assumption is unrealistic since the influence probabilities are usually private information of the individual agents and strategic agents may not reveal them truthfully. Moreover, the influence probabilities could vary significantly with the type of the information flowing in the network and the time at which the information is propagating in the network. In this paper, we use a mechanism design approach to elicit influence probabilities truthfully from the agents. We first work with a simple model, the influencer model, where we assume that each user knows the level of influence she has on her neighbors but this is private information. In the second model, the influencer-influencee model, which is more realistic, we determine influence probabilities by combining the probability values reported by the influencers and influencees. In the context of the first model, we present how VCG (Vickrey-Clarke-Groves) mechanisms could be used for truthfully eliciting the influence probabilities. Our main contribution is to design a scoring rule based mechanism in the context of the influencer-influencee model. In particular, we show the incentive compatibility of the mechanisms when the scoring rules are proper and propose a reverse weighted scoring rule based mechanism as an appropriate mechanism to use. We also discuss briefly the implementation of such a mechanism in viral marketing applications

    An incentive scheme for non-cooperative social networks under the Independent Cascade Model

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    Session 20: Intelligent e-Technology IIn this paper we analyze influence maximization for noncooperative social networks under the Independent Cascade Model. We propose a model of noncooperative nodes and prove some interesting properties of this model. Based on this, we further develop a game-theoretic model to characterize the behavior of noncooperative nodes, and design a Vickrey-Clarke-Groves-like scheme to incentivise cooperation. An advertiser can resolve the negative effect of noncooperation with our proposed solution. Evaluation on large social networks demonstrates the importance of cooperation and the effectiveness of our proposed incentive scheme in maximizing influence. We also discuss the budget allocation between seed nodes activation and incentives to non-seed nodes.published_or_final_versio

    A Survey of Social Network Analysis Techniques and their Applications to Socially Aware Networking

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    Socially aware networking is an emerging research field that aims to improve the current networking technologies and realize novel network services by applying social network analysis (SNA) techniques. Conducting socially aware networking studies requires knowledge of both SNA and communication networking, but it is not easy for communication networking researchers who are unfamiliar with SNA to obtain comprehensive knowledge of SNA due to its interdisciplinary nature. This paper therefore aims to fill the knowledge gap for networking researchers who are interested in socially aware networking but are not familiar with SNA. This paper surveys three types of important SNA techniques for socially aware networking: identification of influential nodes, link prediction, and community detection. Then, this paper introduces how SNA techniques are used in socially aware networking and discusses research trends in socially aware networking

    A Metric for Measuring Customer Turnover Prediction Models

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    The interest for data mining techniques has increased tremendously during the past decades, and numerous classification techniques have been applied in a wide range of business applications. Hence, the need for adequate performance measures has become more important than ever. In this application, a cost-benefit analysis framework is formalized in order to define performance measures which are aligned with the main objectives of the end users, i.e., profit maximization. A new performance measure is defined, the expected maximum profit criterion. This general framework is then applied to the customer churn problem with its particular cost-benefit structure. The advantage of this approach is that it assists companies with selecting the classifier which maximizes the profit. Moreover, it aids with the practical implementation in the sense that it provides guidance about the fraction of the customer base to be included in the retention campaign

    The dominant Law and Economics paradigm regarding “Intellectual Property" – a vehicle or an obstacle for innovation, growth and progress?

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    The term "intellectual property" is a relatively a modern term, first used in its current meaning when the UN established the World Intellectual Property Organization (WIPO) in 1967. Beforehand laws around the world protected various aspects of informational goods - inventions and creations - using separate legal concepts, such as copyright, patents and trademarks, which were not perceived as property rights. This linguistic aspect is by no means anecdotal or marginal as it can be argued that the term "intellectual property" constituted its contemporary meaning including the economic analysis of informational goods and services, as can be demonstrated by the recent call to treat trade secrets not as a contractual agreement but as intellectual property (Epstein, 2005). This paper focuses on the normative analysis of IP rights and criticizes the implicit shift in economic analysis of IP from the incentives paradigm, which is founded upon the public good analysis of neo-classical micro-economic theory, to the new propriety paradigm, which is intellectually founded upon the tragedy of the commons literature. It further criticizes the dominant contemporary Law and Economics writings in this field as pre-assuming information to be an object of property, overlooking its fundamental differences from physical property and thus focusing on its management and maximization of value for its "owners" rather than on its initial justifications and its social value and contribution to innovation, growth and progress.Law; intellectual property; growth; incentives

    Peer influence in network markets: a theoretical and empirical analysis

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    Network externalities spur the growth of networks and the adoption of network goods in two ways. First, they make it more attractive to join a network the larger its installed base. Second, they create incentives for network members to actively recruit new members. Despite indications that the latter "peer effect" can be more important for network growth than the installed-base effect, it has so far been largely ignored in the literature. We address this gap using game-theoretical models. When all early adopters can band together to exert peer influence-an assumption that fits, e.g., the case of firms supporting a technical standard-we find that the peer effect induces additional growth of the network by a factor. When, in contrast, individuals exert peer influence in small groups of size n, the increase in network size is by an additive constant-which, for small networks, can amount to a large relative increase. The difference between small, local, personal networks and large, global, anonymous networks arises endogenously from our analysis. Fundamentally, the first type of networks is "tie-reinforcing," the other, "tie-creating". We use survey data from users of the Internet services, Skype and eBay, to illustrate the main logic of our theoretical results. As predicted by the model, we find that the peer effect matters strongly for the network of Skype users-which effectively consists of numerous small sub-networks-but not for that of eBay users. Since many network goods give rise to small, local networks
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