The Story of Collective Action: The Emergence of Ideological Leaders,Collective Action Network Leaders,and Cross-Sector Network Partners in Civil Society

Collective action and community ecology theories frame this study of longitudinal interorganizational networks in Croatia during the country's political transition. As time progresses toward political stability, grass-roots organizing activities shift through participation in new networks. Although engaged cross-sector communication was important in early stages of the transformation, homophilous partnering emerged as the system stabilized. System stability left room for organizations to exit the collective action network but with costs associated with centralized organizing. Over time, organizations embodied roles as ideological leaders, collective action network leaders, and within-sector network partners. We offer a unique contribution to community ecology and collective action theories with a communication-centered framework that emphasizes the nature of communication in interorganizational networks over a 4-year period.     

A robust decentralized reputation management system for service selection

Reputation mechanism is a novel approach to automate QoS-aware service selection in service oriented computing. The reputation system collects ratings on QoS that consumers feedback and aggregates them to derive a reputation value, which can in turn assist other consumers in service selection in future. However, current approaches fail to combat the malicious ratings and hence the calculated reputation values can be biased severely or even manipulated. Moreover, the centralized management of rating data restricts its application to large open environment. In this paper, we present a robust decentralized reputation system which can resist various unfair ratings and manipulation behaviours. It can evolve and become more mature against malicious ratings with the system running continuously. At last, we experimentally verify the robustness of the proposed approach through a simulation study.     

P2P文件污染及其检测方法研究

为了更好地理解对等网络中的文件污染,介绍了文件污染的背景和分类,分析了文件污染的传播途径及检测方法,描述了用户行为对污染的影响,结合节点信誉系统和对象信誉系统阐述了反污染机制,并对各种方案进行了比较。     

Reputation and efficiency: A non-parametric assessment of America’s top-rated MBA programs

Widely publicized reports of fresh MBAs getting multiple job offers with six-figure annual salaries leave a long-lasting general impression about the high quality of selected business schools. While such spectacular achievement in job placement rightly deserves recognition, one should not lose sight of the resources expended in order to accomplish this result. In this study, we employ a measure of Pareto-Koopmans global efficiency to evaluate the efficiency levels of the MBA programs in Business Week’s top-rated list. We compute input- and output-oriented radial and non-radial efficiency measures for comparison. Among three tier groups, the schools from a higher tier group on average are more efficient than those from lower tiers, although variations in efficiency levels do occur within the same tier, which exist over different measures of efficiency.     

Political YouTube Channel Reputation (PYCR): Development and validation of a multidimensional scale

Although YouTube is driving change in the news and information environment and earning a reputation as an alternative media, there is a lack of research examining what determines people’s reputational judgments on YouTube’s political channels. Based on in-depth interviews with 32 experts and empirical findings from 380 adults, this research identified factors that impact YouTube users’ reputation perception of political channels and developed a scale. The results showed that the Political YouTube Channel Reputation (PYCR) scale comprises four distinctive dimensions: news credibility, political ideology, user-oriented communication, and quality management. The reliability and validity of the scale were assessed, using exploratory and confirmatory analyses and construct validity. The PYCR scale has a variety of potential applications for users, political influencers, and YouTube, and it can serve as a theoretical framework for future empirical research in this novel and emerging area.     

Cooperation in the spatial public goods game with the second-order reputation evaluation

The existence of reputation can significantly promote the level of cooperation within the human population. In the recent years, most of the researches were based on binary image score or first-order evaluation standard. In this paper, we propose a second-order reputation evaluation model, in which the individual's image score will change not only in accordance with his own strategy, but also the reputation value of neighbors. Individuals try to enhance their reputation to cooperate with the surrounding high-reputation individuals, and then becomes an influential individual in the population. The existence of this mechanism renders the individuals who at the edge of the clusters formed by the cooperators to rapidly accumulate their reputation values through the adoption of cooperative strategy, and then the cooperative strategy can be spread widely and rapidly in the whole population. Through extensive numerical simulations, it is clearly indicated that the population cooperation behavior will be obviously improved when the individual's influence factor becomes smaller or the reputation step length increases. The current results are further conducive to understanding the emergence of cooperation in many real world systems.     

基于FIRE模型的Agent联盟研究

FIRE模型改进了SPORAS模型，更适用于开放性的问题求解要求。联盟是多Agent之间一种重要的合作方法。文章将联盟机制引入FIRE模型，通过Agent之间形成联盟对问题求解，能够降低计算复杂度，提高问题求解效率。文章是对多Agent系统联盟的进一步研究，同时改进了Zacharia和Jennings等人关于多Agent系统的信任和名誉模型的研究工作。     

An Automatic User-Recognition Approach Within a Reputation System Using a Nonlinear Hausdorff-Derived Metric

In this paper, we provide an automatic unsupervised recognition technique for Web community user reputations that uses a special nonlinear metric. First we describe the general framework for reputation systems. Then, we propose a feature extraction approach for the reputation system users. The resulting feature vectors (reputations) are clustered with an unsupervised classification algorithm using a nonlinear distance, derived from the Hausdorff metric for sets.     

Reputation-based strategy persistence promotes cooperation in spatial social dilemma

Understanding the emergence and maintenance of cooperation in social dilemma has received a lot of attention. In previous research, many scholars found that the reputation mechanism can promote cooperation, and the variation of reputation is consistent. However, in reality, according to both one's current action and past experiences, every individual's impression from others is modified to varying extent everyday. In other words, the length of duration of the same performance influences the diverse scale of their own reputation fluctuation. Therefore, a reputation-based strategy persistence mechanism, in which the increment of current reputation is determined by the persistence of last strategy, is proposed. Moreover, we introduce a parameter α to illustrate the impact of strategy persistence on reputation variation. The results of simulation show that the new mechanism paves the way for cooperation in evolutionary game, and the smaller α is, the better the mechanism performs.     

Reputation-based co-evolutionary model promotes cooperation in prisoner's dilemma game

Indirect reciprocity is a fascinating topic in the field of social cooperation. In this paper, we propose a novel updating strategy based on the critical reputation-aware calculation. The joint of reputation allows players to make decisions not only on current payoffs but also from a third party, which improves the status of cooperators in the prisoner's dilemma game and provides a possibility for surviving. Experiments show that the discrepancies in initial fitness caused by reputation will support cooperators in occupying a high proportion in communities. Interestingly, we find that the massive scale of reputation fluctuation helps to enhance the cooperative effect, and newly name this character as “quasi-time lag”. The simulations show that the promotion of our proposed mechanism is effective and robust on different network topologies. This work provides a new perspective for the study of the cooperative game.