Mobile CSCL模型的研究与设计

Mobile CSCL是协同学习领域的研究前沿。本文首先综述国内外现有研究成果,阐述了移动学习中社会化交流模式,在此基础上设计了一个MCSCL应用模型,重点研究了模型中服务器端的设备适配、动态内容、信息组织和学习管理四个方面,并通过比较得出MCSCL的三个重要特征:动态内容、预定学习和独立网关,为深入认识与分析无线网络环境下协同学习问题提供了新的研究框架。     

The influence of disposition and social ties on trust in new virtual teammates

With the increased presence of social media tools such as LinkedIn and Facebook, social network information is now commonplace. Social media websites prominently display the social distance or so-called “degrees of separation” among users, effectively allowing people to view their shared social ties with others, including prospective teammates they have not met. Through the presentation and manipulation of social network information, this longitudinal experiment investigated whether dispositional and relational variables contribute to “swift trust” among new virtual teammates. Data from 74 participants were collected to test a path analytic model predicting that social ties and propensity to trust influence perceptions of a new teammate’s trustworthiness (ability, benevolence, and integrity) as well as the willingness to trust that new teammate when given the opportunity to do so. Path analysis indicated good model fit, but showed no significant evidence that social ties or propensity to trust affect perceived trustworthiness at the initial point of team engagement. Additionally, only one component of perceived trustworthiness (perceived ability) and propensity to trust were found to predict trusting behavior towards a new, unknown, teammate.     

校企合作创新网络信任的动态演进分析

从动态角度研究校企合作创新网络中知识转移中信任的演进,构建校企合作创新网络知识转移的非对称演化博弈模型,分析了参数变化对合作创新网络信任的影响,研究表明,收益分配系数、投机收益、知识转移成本、知识转移量等因素影响了校企合作创新网络知识转移中信任的动态演化路径及结果,并通过netlogo仿真,验证了企业和高校知识转移中不同得益情况下策略的选择及信任的演进趋势。     

GDISD团队动态协作信任演化过程研究

异地分布式信息系统开发(GDISD)团队间协作关系是动态发展的,根据组织间信任演进理论,分析分布式开发团队协作关系的发展过程,构建GDISD团队动态协作信任演进的理论模型.从生态学种群增长的视角,运用logistic方程对GDISD团队协作信任演化进行数理分析,使用Jacobi矩阵对方程改进,通过仿真对演化模型进行模拟分析.研究发现,GDISD团队形成与建立的初期,协作方自身信任度的建立对协作信任的发展具有积极作用,并且对信任度的感知积极影射给对方,会加速GDISD团队协作信任的动态演化.研究结果对于分布式团队的管理具有显著的意义.     

一种基于用户行为信任的动态角色访问控制

在基于角色的访问控制(RBAC)模型基础上,引入了属性的概念,增加了用户行为信任级别集合,建立了一种基于用户行为信任评估的动态角色访问控制(UT-DRBAC)模型。对新的模型进行了详细的形式化描述并讨论了模型的授权流程,最后从动态性、信任机制、角色数量和性能方面对模型的优越性进行了分析。新的访问控制模型通过角色属性的动态指派实现了模型授权的动态性,通过把用户信任级别作为一个必需的角色属性实现了基于身份信任和行为信任相结合的访问控制,改变了现有访问控制模型单一基于身份信任的静态授权机制;通过设置角色属性减少角色数量,从而缓解了因角色过多而带来的角色管理问题,同时提高了性能。     

基于QoS 随机性和信任评价的全局动态服务组合

由于Internet环境的开放性和动态性,导致Web服务质量稳定性较差,进而严重影响服务组合的准确度.为此,提出一种基于QoS随机性和信任评价的全局动态服务组合方法.首先,剔除导致客观QoS不稳定的异常值,并估计其真实值;然后,分析服务提供商和用户的信任度,聚合计算主观QoS评价值;最后,结合主、客观QoS约束条件,构建全局动态服务组合优化模型,求解最优组合服务.基于真实和仿真数据的实验结果表明,所提出的方法能够显著提高服务组合的稳定性和准确度.     

Modeling individual trust development in computer mediated collaboration: A comparison of approaches

This research models and investigates individual trust development over time in computer mediated collaboration. Risk, benefit, utility value, effort, power and interest are six factors that influence individual trust development. This paper introduces two new approaches, the scale balance model and the trust spider diagram, to help model and investigate individual trust development over time. A 2 year longitudinal case study is used to investigate individual trust development based on a yearlong student project. 16 student groups participated in the computer mediated collaboration. Survey data were collected at three points throughout the project year and the results are analyzed using the two approaches. Interviews were also conducted at the end of the project. In this research, interesting findings, such as some dynamic features, are revealed by using the methods. Each approach to analyzing individual trust development has its strengths and weaknesses, and using the two together has the benefit of mitigating some weaknesses and combining the strengths. Analyzing trust development over time contributes to enhance computer mediated collaboration in both theoretical research and practical application.     

Modeling and management of profiles and competencies in VBEs

Virtual organization Breeding Environments (VBEs) are long-term clusters/associations of autonomous and geographically dispersed organizations in the market and society. The VBE aims to prepare its member organizations and enhance their readiness for potential involvement in opportunity-based Virtual Organizations (VOs). Organizing/management of profiles is a key activity in VBEs. The need for management of profiles is even larger in medium-size and large-size VBEs (e.g. with more then 50 members), where typically the member organizations do not have the chance of getting to know all others directly. Furthermore, uniform structuring/modeling of the mostly textual content of profiles enables their processing by the software that supports variety of VBE functionality. An important element of the profiles in VBEs is the competency. There is no consensus on the definition of competency and the existing literature associate it with a range of tangible characteristics such as resources and products, as well as intangible characteristics such as knowledge and motivation. This paper introduces and details a unified/generic model for VBE profiles and VBE competencies. It further addresses the design of an adaptable, replicable and sustainable Profile and Competency Management System (PCMS), which is being developed supported by the ontology for profiles and competencies. An approach and mechanism for semi-automated derivation/discovery of elements for organization’s profile and competency from on-line text corpora is also introduced.     

Antecedents and consequences of trust in a social media brand: A cross-cultural study of Twitter

This study extends brand relationship theory to the context of the microblogging platform Twitter. The authors investigate the impact of Twitter trust on users’ intentions to continue using the platform and to “follow” brands that are hosted on Twitter (the trust transfer phenomenon). They also explore the role of perceived self-Twitter personality match in strengthening trust towards the Twitter brand. A cross-cultural American–Ukrainian sample allows to identify potential culture-based differences in brand personality and brand trust concepts. The results show that the positive effect of trust in Twitter on its users’ patronage intentions is robust across two cultures with diverse history and ideology. An important novel finding is the influence of trust in Twitter on patronage intentions towards the businesses hosted on Twitter. However, this relationship reaches statistical significance only in the Ukrainian sample, signaling potential differences in the trust transfer processes in different cultures. The study confirms the role of similarity in personality traits between Twitter users and the Twitter brand in engendering trust in Twitter. The salience of different personality traits in the “personality match – Twitter trust” link for different cultures suggests important implications for global marketers.     

对抗共谋及节点行为动态性的P2P信任模型

针对现有P2P信任模型存在的网络开销大、不能很好地处理节点行为的动态性改变及共谋攻击等问题,提出了一种新的信任模型。通过直接交互节点的局部评价加权其评价可信度计算节点的全局信誉值;采用基于局部评价标准差、局部评价集中度的方法识别和抑制共谋攻击;根据节点行为的改变动态更新其信誉值和评价可信度。仿真实验表明,提出的模型较现有模型在网络开销、抑制共谋攻击和节点行为的动态性等方面有较大改进。     

Modeling of extremal fuzzy dynamic systems. Part II. Extended extremal fuzzy measures on composition products of measurable spaces

This paper continues the investigation of extremal fuzzy measures and their extensions started in Part I. Here, we consider the basic properties of composition extremal fuzzy measures. Several variants of their representations are given. The notion of H-composition over extremal fuzzy measures is introduced, and some algebraic properties of the corresponding structures, which forms the most important part of the fuzzy instrument of modeling extremal fuzzy dynamic systems, are discussed.     

Physical and social presence in collaborative virtual environments: Exploring age and gender differences with respect to empathy

Collaborative virtual environments (CVEs) hold the immense potential of enhancing social inclusion and social support not only in younger but especially also in older people. However, there is still considerably little knowledge about the experiences of elderly when using CVEs. Additionally, there is reason to assume that men and women regardless of their age might also differ in their perceptions of CVEs, with this difference very likely being mediated by empathic abilities. Consequently, the main objective of the current study was to evaluate gender specific experiences of social and physical presence in a group of older (N = 62) and younger adults (N = 62) with respect to possible mediating influences of empathy. Results indicate no differences in physical and social presence between the two age groups, yet they support past findings that men experience more spatial presence, involvement and a higher sense of being there than women. Also, the empathy scale Fantasy considerably mediated gender differences in spatial presence, thus strengthening the theoretical assumption of a relationship between presence and empathy. Implications and future directions of these findings are discussed in detail.     

A domain model of Web recommender systems based on usage mining and collaborative filtering

Considering the increasing demand of multi-agent systems, the practice of software reuse is essential to the development of such systems. Multi-agent domain engineering is a process for the construction of domain-specific agent-based reusable software artifacts, like domain models, representing the requirements of a family of multi-agent systems in a domain, and frameworks, implementing reusable agent-based design solutions to those requirements. This article describes the domain modeling tasks of the MADEM methodology and a case study on the application of GRAMO, a MADEM technique, for the construction of the domain model of ONTOWUM, specifying the common and variable requirements of a family of Web recommender systems based on usage mining and collaborative filtering.     

A survey of trust in computer science and the Semantic Web

Trust is an integral component in many kinds of human interaction, allowing people to act under uncertainty and with the risk of negative consequences. For example, exchanging money for a service, giving access to your property, and choosing between conflicting sources of information all may utilize some form of trust. In computer science, trust is a widely used term whose definition differs among researchers and application areas. Trust is an essential component of the vision for the Semantic Web, where both new problems and new applications of trust are being studied. This paper gives an overview of existing trust research in computer science and the Semantic Web.     

On consensus reaching process based on social network analysis in uncertain linguistic group decision making: Exploring limited trust propagation and preference modification attitudes

This paper explores a limited trust propagation-based consensus model considering individual attitude for preference modification in a social networked setting with uncertain preference information. To examine the construction of complete linkages, and the status of decision makers in group decision making, it is assumed that the group size and network density will affect the scale of mediators in the propagation process, then a definition of limited trust propagation is proposed and the propagation efficiency can be introduced. On this basis, we obtain missing trust relationships and individual centrality in network. In the process of consensus reaching, both the decision maker’s original preference and recommendation advice are considered for flexibly modeling the preference modification process: the individual attitude toward modification is determined by a newly introduced measure of comprehensive relative out-degree centrality, showing the degree of willingness to adjust assessments. When the willingness is too low to reach the preset consensus level, a multi-objective programming model is designed to improve the consensus as much as possible. Moreover, the proposed feedback mechanism narrows the individual acceptable modification range based on the previous adjustment rule, so as to simulate the personalized and targeted decision behavior. To guarantee obtaining a collective aggregated preference in a logical and precise manner, a two-stage optimization model composing of comprehensive relative in-degree centrality-based information aggregation and best consistency-based uncertainty elimination, is proposed. A numerical example and comparative analyses are performed to show the validity and feasibility of the proposed model.     

Examining the impact of privacy, trust and risk perceptions beyond monetary transactions: An integrated model

Much interest in privacy and trust studies is about shopping, but privacy research in other forms of online activities is beginning to emerge. This study examined the antecedents of privacy, trust and risk as well as their joint effect on two similar but fundamentally different activities: online transactions and retrieval of privileged information. Both activities involve the delivery of private user information, but the latter gives some leeway for users to control (or even falsify) their true identity. User shopping experience in the present study moderated the relationships and strengths of constructs. The effect of Internet literacy, social awareness and disposition to trust on privacy concern and trust was weaker for experienced shoppers. Privacy concern, trust and risk assessment played a lesser role on the two activity variables for those who were more experienced. Perceived privacy risk stood out as a strong antecedent for respondents in both experience groups, but the effect of Internet literacy, social awareness and disposition on trust was statistically insignificant for the same group. Further practical and managerial implications are provided.     

Investigating individual trust in semi-virtual collaboration of multicultural and unicultural teams

This study aims to investigate individual's trust development for semi-virtual collaboration teams with multicultural and unicultural background. We aim to explore whether the trust levels in multicultural and unicultural semi-virtual groups will be the same, how trust develops over time and what the corresponding factors to the trust development are. In order to answer the questions, a longitudinal case study was conducted in unicultural and multicultural teams. We have taken survey for 144 participants over three stages, as well as interviewed 64 participants. Results of the analysis of the survey data firstly show that no significant difference exists between multicultural and unicultural groups. Then, two factors, collaboration process and clear task help explain this phenomenon. However, the trust development of multicultural groups shows instability and keeps decreasing over time, while unicultural groups behave differently. We found that language, values and habitual behavior lead to the differences in these two types of groups.     

Modeling and analyzing dynamic social networks for behavioral pattern discovery in collaborative design

As a newly-developed information exchange and management platform, Building Information Modeling (BIM) is altering the way of collaboration among multi-engineers for civil engineering projects. During the BIM implementation, a large number of event logs are automatically generated and accumulated to record details of the model evolution. For knowledge discovery from huge logs, a novel BIM event log mining approach based on the dynamic social network analysis is presented to examine designers’ performance objectively, which has been verified in BIM event logs about an ongoing year-long design project. Relying on meaningful information extracted from time-stamped logs, networks on the monthly interval are built to graphically represent information and knowledge sharing among designers. Special emphasis is put on measuring designers’ influence by a defined new metric called “impact score”, which combines the k-shell method and 1-step neighbors to achieve comparatively low computational cost and high accurate ranking. Besides, an emerging machine learning algorithm named CatBoost is utilized to predict designers’ influence intelligently by learning features from both network structure and human behavior. It has been found that twelve networks can be easily distinguished into two collaborative patterns, whose characteristics in both network structures and designers’ behaviors are significantly different. The most influential designers are similar within the same group but varied from different groups. Extensive analytical results confirm that the method can potentially serve as month-by-month feedback to monitor the complex modeling process, which further supports managers to realize data-driven decision making for better leadership and work plan towards an optimized collaborative design.     

The effects of social media based brand communities on brand community markers,value creation practices,brand trust and brand loyalty

Social media based brand communities are communities initiated on the platform of social media. In this article, we explore whether brand communities based on social media (a special type of online brand communities) have positive effects on the main community elements and value creation practices in the communities as well as on brand trust and brand loyalty. A survey based empirical study with 441 respondents was conducted. The results of structural equation modeling show that brand communities established on social media have positive effects on community markers (i.e., shared consciousness, shared rituals and traditions, and obligations to society), which have positive effects on value creation practices (i.e., social networking, community engagement, impressions management, and brand use). Such communities could enhance brand loyalty through brand use and impression management practices. We show that brand trust has a full mediating role in converting value creation practices into brand loyalty. Implications for practice and future research opportunities are discussed.