虚拟知识社区的综合访问控制模型研究

为了防止非法社区成员进入社区和合法社区成员对知识社区知识资源的非法使用,构建了由用户资质、社区知识资源和综合控制策略等组成的虚拟知识社区的综合访问控制模型.利用基于属性的访问控制思想,从用户角色、用户综合信誉、用户拥有的知识货币量以及知识单价,知识交易量、知识满意度等侧面建立用户资质和社区知识资源模型,依据该模型,利用决策表,表达了虚拟知识社区的综合访问控制策略.结合案例比较结果表明了综合访问控制模型的可行和策略的有效性.     

微博网络上的重叠社群发现与全局表示

微博网络是新兴的覆盖海量用户、涉及广泛话题并具有复杂重叠社群结构的多模网络。在深入研究微博网络各类实体和属性内在联系的基础上,提出了以用户-话题关系为主要划分原则的重叠社群表达模型及相应的社群结构发现算法。该方法不仅考虑网络中的用户-话题关系,还融合了这一网络特有的用户关注关系、博文评论与转发关系等所形成的复合网络关系。同时,改进了传统的社群隶属矩阵表述模型,通过引入虚拟社群,使隶属矩阵不仅合理反映个体对社群的隶属度,同时标识了个体在社群中的核心度。通过基于新浪微博数据集的实验验证,结果表明：该模型与方法能够高效合理地刻画该数据集包含的重叠社群结构,实验结果具有良好的可解释性,所提出的模型和算法可以有效地应用于类似多模网络社群划分和演化分析研究中。     

To give or to receive? Factors influencing members’ knowledge sharing and community promotion in professional virtual communities

Professional virtual communities (PVCs) bring together geographically dispersed, like-minded people to form a network for knowledge exchange. To promote knowledge sharing, it is important to know why individuals choose to give or to receive knowledge with other community members. We identified factors that were considered influential in increasing community knowledge transfer and examined their impact in PVCs. Data collected from 323 members of two communities were used in our structural equation modeling (SEM). The results suggested that norm of reciprocity, interpersonal trust, knowledge sharing self-efficacy, and perceived relative advantage were significant in affecting knowledge sharing behaviors in PVCs. The knowledge contributing and collecting behaviors were positively related to knowledge utilization. Furthermore, while the collecting behavior had a significant effect on community promotion, the influence of contributing behavior on community promotion was limited.     

Determinants of knowledge seeking in professional virtual communities

As knowledge management systems within organisations, professional virtual communities (PVCs) are popular knowledge-seeking tools, which bring together geographically dispersed members from outside of the organisations. An increasing number of employees use PVCs for knowledge seeking, knowledge exchange and problem solving at work. Why do members choose to receive knowledge from other community members in PVCs needs to be understood. This paper extends Ajzen's [1991. The theory of planned behaviour. Organizational Behavior and Human Decision Processes, 50 (2), 179–211] theory of planned behaviour to elicit external beliefs in terms of personal motivation, as well as technological and social factors, and to examine the relative importance of these factors. According to this study's online survey of 323 members in three PVCs, the results show that the significance of beliefs, such as system quality, compatibility, trust, knowledge growth and knowledge quality, in creating positive attitudes towards knowledge seeking. Community identification is shown as a salient belief for the subjective norms of knowledge seeking. System quality and resource availability are revealed as important determinants for perceived behavioural control of knowledge seeking. Knowledge-seeking intention is based on the attitude towards knowledge seeking and the subjective norm of knowledge seeking, whereas knowledge-seeking behaviour is solely determined by knowledge-seeking intention. Implications for research and practice are discussed.     

Internet aggression in online communities: a contemporary deterrence perspective

Internet users' activities are critical to the development and success of Web 2.0 systems, such as online communities. Within the community's participation, knowledge sharing, and communications, users may conduct aggressive behaviors that would have a negative impact on that online community. This study investigates factors that affect Chinese users' aggression intention in online communities. Research findings show that online aggression can be inhibited by internal deterrents of face saving and moral beliefs, which may be enhanced through implementation of consequences from an effective community policy and peer pressure among community members. Differences in the effects of the deterrence measures exist between younger and older users. This paper contributes theoretically and empirically to Web 2.0 research and has practical implications for virtual community management.     

Ontology-based empirical knowledge verification for professional virtual community

A professional virtual community provides an interactive platform for enterprise experts to create and share their empirical knowledge cooperatively, and the platform contains a tremendous amount of hidden empirical knowledge that knowledge experts have preserved in the discussion process. Therefore, enterprise knowledge management highly prioritises how to verify the empirical knowledge effectively before archiving it into enterprise knowledge repository for reuse. This work develops a novel scheme of ontology-based empirical knowledge verification for professional virtual community to assist domain experts in a professional virtual community to verify the logics of empirical knowledge, thus ensuring the quality of empirical knowledge and providing accurate knowledge decision support for knowledge workers. In particular, this work has the following objectives: propose an empirical knowledge verification model for a professional virtual community, design an ontology-based empirical knowledge verification process, develop techniques related to the ontology-based empirical knowledge verification and implement an ontology-based empirical knowledge verification mechanism with an illustrative example of securities trading. Results of this study facilitate efforts within the professional virtual community to verify empirical knowledge in order to provide knowledge workers with logic-correct empirical knowledge for decision support.     

How do entrepreneurs learn and engage in an online community-of-practice? A case study approach

This paper investigates the ways in which entrepreneurs use communities of practice (CoPs) to express themselves, using narrative theory and rhetorical analysis, to gain insight into an electronic social network medium, namely, YoungEntrepreneur.com. In particular, the study focuses on CoPs themes, including why entrepreneurs engage in CoPs, what role the moderators and resident entrepreneurs can play in managing online CoPs, on communication rituals of the knowledge sharing through interactivity, and on ‘how to develop an intervention’ to maintain and stimulate entrepreneurs for engaging in an online community. Findings reveal that the topic title plays a major role in attracting people. Successful topics with successful conclusions (in terms of the original query that was answered) will not necessarily get high responses and vice versa. It is observed that the domain expert does not play a big role in keeping the discussion going. Finally, the study also discovered that entrepreneurs like to communicate in a story telling genre. A comprehensive set of engagement measurement tools are introduced to effectively measure the engagement in a virtual CoP, along with a classification to define and categorise discourse of messages in terms of content and context, which allow practitioners to understand the effectiveness of a social networking site.     

基于相似性链路预测的大众生产演化特征

结合大众生产虚拟社区的静态结构与动态演化机理,提出择优机制与间接推荐是大众生产虚拟社区的显著演化特征。针对Wiki票选管理员的行为网络进行分析,结果显示虚拟社区贡献者的选择行为具有较强异质性特征。采用基于局部信息相似性的链路预测方法对网络潜在链接特征进行分析,得出择优指标值在各项指标中得分最高的结果。运用基于路径相似性的链路预测方法,证明相比其他路径与随机游走指标,Katz指标有更好的预测结果,说明间接推荐是虚拟社区演化过程的重要特征。     

一种加权稠密子图社区发现算法

目前,针对复杂网络的社区发现算法大多仅根据网络的拓扑结构来确定社区,然而现实复杂网络中的边可能带有表示连接紧密程度或者可信度意义的权重,这些先验信息对社区发现的准确性至关重要.针对该问题,提出了基于加权稠密子图的重叠聚类算法（overlap community detection on weighted networks,简称OCDW）.首先,综合考虑网络拓扑结构及真实网络中边权重的影响,给出了一种网络中边的权重定义方法;进而给出种子节点选取方式和权重更新策略;最终得到聚类结果.OCDW算法在无权网络和加权网络都适用.通过与一些经典的社区发现算法在9个真实网络数据集上进行分析比较,结果表明算法OCDW在F度量、准确度、分离度、标准互信息、调整兰德系数、模块性及运行时间等方面均表现出较好的性能.     

Virtual communities as a resource for the development of OSS projects: the case of Linux ports to embedded processors

Open source software (OSS) projects represent a new paradigm of software creation and development based on hundreds or even thousands of developers and users organised in the form of a virtual community. The success of an OSS project is closely linked to the successful organisation and development of the virtual community of support. The main objective of this article is to analyse the activity of virtual communities. Social network analysis is employed to analyse Linux ports to embedded processors as a case study to achieve this aim. The obtained results confirm the necessity of structuring the virtual community with a selection of active developers and core members to promote community activity and attract peripheral users, expanding the impact of the underlying software. The obtained result will be useful for the software industry migrating to the open source software paradigm.     

How virtual community participation influences consumer loyalty intentions in online shopping contexts: an investigation of mediating factors

Extant studies generally recognise that virtual community building is an effective marketing programme for forging deep and enduring affective bonds with consumers. This study extends previous research by proposing and testing a model that investigates key mediating processes (via trust, satisfaction and identification) that underlie the relationship between virtual community participation and consumer loyalty intentions. The authors test the hypotheses using data obtained from three large online retailing stores. Virtual community participation significantly enhances loyalty intentions, through both social mechanisms (via community identification) and psychological mechanisms (via trust and satisfaction). Moreover, the findings provide insights into the complex relationship between the two mechanisms in online shopping settings. Community identification is a pivotal factor for enhancing customer loyalty intentions. The results advance understanding of the process by which virtual community building facilitates the development of business-to-consumer relationships in the computer-mediated environment. The authors discuss the managerial implications of the findings, as well as avenues for further research.     

Understanding knowledge contributors’ satisfaction in transactional virtual communities: A cost–benefit trade-off perspective

This study investigates knowledge contributors’ satisfaction with a distinct type of virtual communities (i.e., transactional virtual communities, TVCs), where knowledge sharing is guided mainly under the principle of economic exchange, and cost–benefit tradeoff is the primary motive for knowledge sharing. Drawing upon the goal attainment theory, we examine the effects of two types of benefits (i.e., extrinsic and intrinsic) and two types of costs (i.e., actual and opportunity) on knowledge contributors’ satisfaction, and highlight the mediating role of perceived net goal attainment. A field survey with 205 subjects in a TVC in China is conducted to test the research model.     

Exploring knowledge contribution from an OCB perspective

As participation in virtual community becomes popular, it is important to know how to encourage individuals to contribute actively and assist other members share their expertise. Through the lens of organizational citizenship behavior (OCB), we explored the factors that facilitate voluntary knowledge sharing in a virtual community. We examined OCB in online gaming communities in which various behaviors can contribute to the community (the team) or to individuals (team members). Our aim was to gain insight into ways of creating an environment that facilitated voluntary sharing of knowledge. Our findings suggested that effective leader–member exchange relationships, the attractiveness of the group to individuals, and affection similarity were important in establishing a virtual environment within which voluntary contributions could be promoted effectively. In addition, our study suggested that better quality leader–member exchange relationships and positive affection toward the virtual team enhanced OCB.     

A Community Structure‐Based Approach for Network Immunization

We propose a community structure‐based approach that does not require community labels of nodes, for network immunization. Social networks have been widely used as daily communication infrastructures these days. However, fast spreading of information over networks may have downsides such as computer viruses or epidemics of diseases. Because contamination is propagated among subgraphs (communities) along links in a network, use of community structure of the network would be effective for network immunization. However, despite various research efforts, it is still difficult to identify ground‐truth community labels of nodes in a network. Because communities are often interwoven through intermediate nodes, we propose to identify such nodes based on the community structure of a network without requiring community labels. By regarding the community structure in terms of nodes, we construct a vector representation of nodes based on a quality measure of communities. The distribution of the constructed vectors is used for immunizing intermediate nodes among communities, through the hybrid use of the norm and the relation in the vector representation. Experiments are conducted over both synthetic and real‐world networks, and our approach is compared with other network centrality‐based approaches. The results are encouraging and indicate that it is worth pursuing this path.     

本体驱动的动态虚拟社区知识通信

知识通信是实现语义Web的有效途径之一。该文给出知识通信的定义和特点,构建了基于动态虚拟社区的P2P知识通信架构;为实现高效知识路由,建立了基于本体的任务元知识库、任务实例库、规则库、本体知识库,设计了具有发现、协调和定位服务资源等功能的路由服务Agent,建立了本体驱动、分散控制的快速、准确、高效的知识路由机制。     

基于深度稀疏自动编码器的社区发现算法

社区结构是复杂网络的一个重要特征,社区发现对研究网络结构有重要的应用价值.k-均值等经典聚类算法是解决社区发现问题的一类基本方法.然而,在处理网络的高维矩阵时,使用这些经典聚类方法得到的社区往往不够准确.提出一种基于深度稀疏自动编码器的社区发现算法CoDDA,尝试提高使用这些经典方法处理高维邻接矩阵进行社区发现的准确性.首先,提出基于跳数的处理方法,对稀疏的邻接矩阵进行优化处理.得到的相似度矩阵不仅能反映网络拓扑结构中相连节点间的相似关系,同时能反映不相连节点间的相似关系.接着,基于无监督深度学习方法,构建深度稀疏自动编码器,对相似度矩阵进行特征提取,得到低维的特征矩阵.与邻接矩阵相比,特征矩阵对网络拓扑结构有更强的特征表达能力.最后,使用k-均值算法对低维特征矩阵聚类得到社区结构.实验结果显示,与6种典型的社区发现算法相比,CoDDA算法能够发现更准确的社区结构.同时,参数实验结果显示,CoDDA算法发现的社区结构比直接使用高维邻接矩阵的基本k-均值算法发现的社区结构更为准确.     

The new neighbourhood in the internet era: network communities serving local communities

The past two decades have witnessed many attempts to transform online communities in new neighbourhoods of the Internet era. In particular, one of the most interesting applications of Internet Technologies in this field have been ‘network communities’, that differ from online communities because they refer to a specific territory and, for this reason, serve as a social catalyst for the corresponding territorial community. Network communities, as virtual neighbourhoods, have the purpose of allowing a better understanding of physical ones, contributing to the creation and the proliferation of services most suited to the needs of residents. For this reason, municipalities and local governments should consider the opportunity to exploit network communities as useful tools for local community management. Following this lead, this article analyses a real case study and highlights the existence of a positive correlation between a constructive utilisation of a network community by its members, their sense of community and the degree of their involvement in local problems.     

Knowledge processes in virtual teams: consolidating the evidence

This article takes stock of the current state of research on knowledge processes in virtual teams (VTs) and consolidates the extent research findings. Virtual teams, on the one hand, constitute important organisational entities that facilitate the integration of diverse and distributed knowledge resources. On the other hand, collaborating in a virtual environment creates particular challenges for the knowledge processes. The article seeks to consolidate the diverse evidence on knowledge processes in VTs with a specific focus on identifying the factors that influence the effectiveness of these knowledge processes. The article draws on the four basic knowledge processes outlined by Alavi and Leidner (2001 Alavi, M.Leidner, D.E., 2001. Review: knowledge management and knowledge management systems: conceptual foundations and research issues. MIS Quarterly, 25 (1), 107–136. doi: 10.2307/3250961[Crossref], [Web of Science ®] , [Google Scholar]) (i.e. creation, transferring, storage/retrieval and application) to frame the investigation and discuss the extent research. The consolidation of the existing research findings allows us to recognise the gaps in the understanding of knowledge processes in VTs and identify the important avenues for future research.     

LPX: Overlapping community detection based on X‐means and label propagation algorithm in attributed networks

Traditional community detection methods in attributed networks (eg, social network) usually disregard abundant node attribute information and only focus on structural information of a graph. Existing community detection methods in attributed networks are mostly applied in the detection of nonoverlapping communities and cannot be directly used to detect the overlapping structures. This article proposes an overlapping community detection algorithm in attributed networks. First, we employ the modified X‐means algorithm to cluster attributes to form different themes. Second, we employ the label propagation algorithm (LPA), which is based on neighborhood network conductance for priority and the rule of theme weight, to detect communities in each theme. Finally, we perform redundant processing to form the final community division. The proposed algorithm improves the X‐means algorithm to avoid the effects of outliers. Problems of LPA such as instability of division and adjacent communities being easily merged can be corrected by prioritizing the node neighborhood network conductance. As the community is detected in the attribute subspace, the algorithm can find overlapping communities. Experimental results on real‐attributed and synthetic‐attributed networks show that the performance of the proposed algorithm is excellent with multiple evaluation metrics.     

基于图卷积神经网络的在线社区行为预测

在线知识社区中,问题的回答可以看作多个回答者用户(领域专家)之间的协作行为。协作行为在知识社区中通常是大规模地发生,协作行为预测对在线社交中领域专家的推荐有重要意义。基于在线知识社区中回答者用户之间的协作行为,构建以领域专家为节点,以他们之间的协作回答关系为边的协作网络。由于协作行为网络的构建与社交关系网络的构建上结构的相似性,可以将协作行为预测构建为协作网络中的链接预测问题。通过构建基于图卷积神经网络的链接预测模型,对在线知识社区中回答者用户的协作行为进行预测。基于“知乎”数据集的实验验证,与其他经典的预测方法进行比较时,发现提出的方法能够更加有效地预测在线知识社区中回答者用户之间的协作行为。