Guanxi networks and members' effectiveness in Chinese work teams: Mediating effects of trust networks

The present study examined 33 teams with a total of 206 team members (excluding team leaders) to explore the effects of intrateam guanxi and trust networks on individual effectiveness in Taiwan. Guanxi networks included non-job, departmental and past team networks, while trust networks included affective and cognitive trust networks. Results showed that: (i) guanxi networks could better explain members' effectiveness compared with relational demography, and different guanxi networks had different effects; (ii) the more central an individual's position was in the cognitive trust network, the higher the individual's effectiveness; (iii) the past team guanxi network of a team member displayed a positive effect on the centrality of cognitive trust network, while non-job and departmental guanxi networks showed negative effects; and (iv) the effects of members' guanxi networks on individual effectiveness were mediated by the centrality of trust networks.     

注意网络间的关系及其心理与生理机制

Posner和Petersen把注意系统分为警觉、定向和执行控制三个网络。注意网络测验及其变式是研究注意网络间关系的主要工具。生物化学、神经影像和行为研究从神经递质广泛调节、脑功能区共享、注意资源竞争和认知策略调节的角度证明了三个注意网络之间既相互独立又有机统一的关系。测量信度低、定义模糊成为注意网络及其关系的研究中亟待解决的问题。将来的研究需要改进测量工具, 并考虑注意网络的子成分对网络间关系的影响。     

Causality, Propensity, and Bayesian Networks

This paper investigates the relations between causality and propensity. Aparticular version of the propensity theory of probability is introduced, and it is argued that propensities in this sense are not causes. Some conclusions regarding propensities can, however, be inferred from causal statements, but these hold only under restrictive conditions which prevent cause being defined in terms of propensity. The notion of a Bayesian propensity network is introduced, and the relations between such networks and causal networks is investigated. It is argued that causal networks cannot be identified with Bayesian propensity networks, but that causal networks can be a valuable heuristic guide for the construction of Bayesian propensity networks.     

Are support and social comparison compatible? Individual differences in the multiplexity of career‐related social networks

Social networks are crucial for helping people in their careers. Moreover, social identity is reflected in and influenced by individuals’ networks. To date, there is little knowledge on how these different functions of networks might interact. A survey in which 450 individuals provided information on 2,499 contacts in their social networks indicated both multiplexity and segmentation in networks. Contacts tended either to provide psychosocial support only or to provide instrumental support and serve as a standard for social comparison. The segmentation was stronger for individuals with an independent career orientation than for promotion‐oriented individuals. These findings contribute to the literature on social networks and careers by providing insights into how career orientation affects the multiplexity in career‐related social networks.     

Networks of prospective thoughts: The organisational role of emotion and its impact on well-being

Recent research has shown that many prospective thoughts are organised in networks of related events, but the relational dimensions that contribute to the formation of such networks are not fully understood. Here, we investigated the organisational role of emotion by using cues of different valence for eliciting event networks. We found that manipulating the emotional valence of cues influenced the characteristics of events within networks, and that members of a network were more similar to each other on affective components than they were to members of other networks. Furthermore, a substantial proportion of events within networks were part of thematic clusters and cluster membership significantly modulated the impact of represented events on current well-being, in part through an intensification of the emotion felt when thinking about these events. These findings demonstrate that emotion contributes to the organisation of future thoughts in networks that can affect people's well-being.     

Sex differences in the structure and stability of children's playground social networks and their overlap with friendship relations

Gender segregated peer networks during middle childhood have been highlighted as important for explaining later sex differences in behaviour, yet few studies have examined the structural composition of these networks and their implications. This short‐term longitudinal study of 119 children (7–8 years) examined the size and internal structure of boys' and girls' social networks, their overlap with friendship relations, and their stability over time. Data collection at the start and end of the year involved systematic playground observations of pupils' play networks during team and non‐team activities and measures of friendship from peer nomination interviews. Social networks were identified by aggregating play network data at each time point. Findings showed that the size of boy's play networks on the playground, but not their social networks, varied according to activity type. Social network cores consisted mainly of friends. Girl's social networks were more likely to be composed of friends and boys' networks contained friends and non‐friends. Girls had more friends outside of the social network than boys. Stability of social network membership and internal network relations were higher for boys than girls. These patterns have implications for the nature of social experiences within these network contexts.     

青少年问题性社交网络使用

青少年问题性社交网络使用是世界范围内受到普遍关注的问题。问题性社交网络使用常被称作“社交网络成瘾”、“病理性社交网络使用”或“社交网络过度使用”, 概念和界定标准还没有达成一致看法。青少年合理的社交网络使用对促进社交关系的建立、维持和发展有积极意义, 但问题性社交网络使用却对青少年的身心发展产生消极影响。对青少年问题性社交网络使用发生机制的探讨, 将为问题性社交网络的干预引导提供依据。未来的研究应对问题性社交网络使用的概念和界定标准进行澄清, 用多维视角的方法开展问题性社交网络使用发生机制的深入研究, 加强对问题性社交网络使用的理论建构和干预研究。     

Social capital and refugee resettlement: The social networks of refugees in Canada

Survey data from a large sample of recent refugees (N=525) living in Canada are used to profile the size and structure of refugees' social networks and to highlight the value (or function) of such social capital in the resettlement process. Despite the traumas associated with becoming a refugee, most adult refugees remain part of at least some familial networks. A large minority are connected with more extented family networks, and almost half plant to build these networks by sponsoring other family members. As resettlement continues, more extensive extra-familial networks involving neighbours, co-workers and employers, other community members, and a wide range of service providers are constructed. These many formal and informal social networks are extremely valuable, providing much-needed support and assistance when refugees are faced with financial, employment, personal, or health problems. Policy challenges arising from these findings are discussed.     

The structure and function of social support networks in families with handicapped children

Three structural characteristics of social support networks (size, density, and boundary density) and two relationship characteristics (reciprocity and dimensionality) were assessed in a sample of 56 families with a child with spina bifida and 53 matched comparison families. The results indicate that social networks of families with handicapped children tended to be smaller than the networks of comparison families, particularly with regard to mothers' total and friendship networks. The networks of families with handicapped children were more dense as well. As predicted, there was greater boundary density in spousal networks in families with handicapped children. Differences in network reciprocity were inconclusive while the results indicate that families with handicapped children tended to rely more heavily upon multidimensional network contacts than did comparison families. The results are discussed in light of our understanding of stress, social support, and the social ecological context of families.     

Does Intraorganizational Network Embeddedness Improve Salespeople’s Effectiveness? A Task Contingency Perspective

Using a two-phase research methodology, this study investigates the relationship between salespeople’s intraorganizational network embeddedness and their sales effectiveness. Following the findings of the exploratory research, we first distinguish salespeople’s intraorganizational networks on the basis of their content—work versus social networks—and their tie activation frequency. Next, we focus on three main sales tasks, opportunity-identification, solution-creation, and closing the deal, and uncover that overcoming the challenges of each sales task requires mobilizing particular intraorganizational resources. We show that work and social networks give access to different sets of resources, and we develop a contingency model that explains which networks and network ties are likely to be more instrumental for salespeople’s effectiveness at each sales task. In the second phase of the research, we test the contingency model using a sociometric method. The results indicate that for effectiveness in opportunity-identification, social as opposed to work networks are most instrumental. For effectiveness in solution-creation, work rather than social networks are more critical. And for closing the deal, both work networks and social networks are important. Furthermore, salespeople who have frequently activated network ties are consistently more effective than salespeople who may have many ties but who activate them less frequently.     

Adaptive rewiring in weighted networks

Human connectome studies suggest that the brain has a modular small world network structure with rich-club effect. Such structure emerges spontaneously in simple model neural networks, (e.g. coupled maps), through adaptive rewiring according to the dynamic functional connectivity. The utility of adaptive rewiring has so far exclusively been demonstrated for unweighted networks; it is anything but guaranteed to work as well for weighted networks. We investigate adaptive rewiring in weighted networks, comparing various right-skewed, symmetrical, and left-skewed fixed weight distributions. We examine how network clustering, path length, modularity, and rich club coefficients develop for weakly, intermediate and strongly coupled networks. At low coupling strength, the weight distribution, as well as episodes of functional synchrony, have a significant effect on network evolution. With increased coupling strengths, all weighted networks robustly develop architectures similar to the unweighted ones. Adaptive rewiring appears relatively ineffective in networks with (biologically implausibly) extreme right-skewed weight distributions but performed most economically in biologically plausible log-normal distributions.     

Fibring Argumentation Frames

This paper is part of a research program centered around argumentation networks and offering several research directions for argumentation networks, with a view of using such networks for integrating logics and network reasoning. In Section 1 we introduce our program manifesto. In Section 2 we motivate and show how to substitute one argumentation network as a node in another argumentation network. Substitution is a purely logical operation and doing it for networks, besides developing their theory further, also helps us see how to bring logic and networks closer together. Section 3 develops the formal properties of the new kind of network and Section 4 offers general discussion and comparison with the literature.     

Social Networks and Subjective Well-Being: A Comparison of Australia,Britain, and China

This paper is a comparative study of formal and informal social networks and their effects on subjective well-being in Australia, Britain, and China. Formal social networks are measured by group affiliations, and informal social networks are measured by personal connections with kin, friends, and acquaintances. An analysis of the national representative sample surveys from the three countries shows that the formal networks are of notable importance in increasing people’s subjective well-being in Britain and urban China, but the informal networks have much greater impacts in all three countries, particularly in rural China. We propose a cultural–structural interaction framework to explain the observed differences in the network influence on subjective well-being in the three countries.     

Cortical memory mechanisms and language origins

We have previously proposed that cortical auditory-vocal networks of the monkey brain can be partly homologized with language networks that participate in the phonological loop. In this paper, we suggest that other linguistic phenomena like semantic and syntactic processing also rely on the activation of transient memory networks, which can be compared to active memory networks in the primate. Consequently, short-term cortical memory ensembles that participate in language processing can be phylogenetically tracked to more simple networks present in the primate brain, which became increasingly complex in hominid evolution. This perspective is discussed in the context of two current interpretations of language origins, the "mirror-system hypothesis" and generativist grammar.     

Learning Continuous Probability Distributions with Symmetric Diffusion Networks

In this article we present symmetric diffusion networks, a family of networks that instantiate the principles of continuous, stochastic, adaptive and interactive propagation of information. Using methods of Markovion diffusion theory, we formalize the activation dynamics of these networks and then show that they can be trained to reproduce entire multivariate probability distributions on their outputs using the contrastive Hebbion learning rule (CHL). We show that CHL performs gradient descent on an error function that captures differences between desired and obtained continuous multivariate probability distributions. This allows the learning algorithm to go beyond expected values of output units and to approximate complete probability distributions on continuous multivariate activation spaces. We argue that learning continuous distributions is an important task underlying a variety of real-life situations that were beyond the scope of previous connectionist networks. Deterministic networks, like back propagation, cannot learn this task because they are limited to learning average values of independent output units. Previous stochastic connectionist networks could learn probability distributions but they were limited to discrete variables. Simulations show that symmetric diffusion networks can be trained with the CHL rule to approximate discrete and continuous probability distributions of various types.     

社会支持网络对城市贫困人口身心状况的影响

摘 要 通过对天津贫困人口的随机样本的分析,探讨了社会支持的数量、质量和社会支持网的网络结构对贫困人口的身心状况的影响。研究发现,社会支持的数量对城市贫困人口的身心状况没有影响。社会支持的质量则对贫困人口的身心状况有正向的影响。社会支持网的异质性越高,趋同性越低,生活满意度越高。这些指标对身体健康则没有影响。但网络中高于中心成员收入水平的越多,身心状况越差。     

Organizational network perceptions versus reality: A small world after all?

Given the complexity of organizing and keeping track of even a small organizational network, boundedly rational people may have learned to use small world principles in perceiving friendship networks: arrange people in dense clusters, and connect the clusters with short paths. Analysis of 116 perceived friendship networks from four different organizations showed that these perceived networks exhibited greater small world properties than the actual friendship networks. Further, people perceived more friendship clustering than actually existed, and attributed more popularity and brokerage to the perceivedly-popular than to the actually-popular.     

Is it worth generating rules from neural network ensembles?

Although many authors generated comprehensible models from individual networks, much less work has been done in the explanation of ensembles. DIMLP is a special neural network model from which rules are generated at the level of a single network and also at the level of an ensemble of networks. We applied ensembles of 25 DIMLP networks to several datasets of the public domain and a classification problem related to post-translational modifications of proteins. For the classification problems of the public domain, the average predictive accuracy of rulesets extracted from ensembles of neural networks was significantly better than the average predictive accuracy of rulesets generated from ensembles of decision trees. By varying the architectures of DIMLP networks we found that the average predictive accuracy of rules, as well as their complexity were quite stable. The comparison to other rule extraction techniques applied to neural networks showed that rules generated from DIMLP ensembles gave very good results. In the last problem related to bioinformatics, the best result obtained by ensembles of DIMLP networks was also significantly better than the best result obtained by ensembles of decision trees. Thus, although neural networks take much longer to train than decision trees and also rules are generated at a greater computational cost (however, still polynomial), at least for several classification problems it was worth using neural network ensembles, as extracted rules were more accurate, on average. The DIMLP software is available for PC-Linux under http://us.expasy.org/people/Guido.Bologna.html.     

Encoding Shape and Spatial Relations: The Role of Receptive Field Size in Coordinating Complementary Representations

An effective functional architecture facilitates interactions among subsystems that are often used together. Computer simulations showed that differences in receptive field sizes can promote such organization. When input was filtered through relatively small nonoverlapping receptive fields, artificial neural net-works learned to categorize shapes relatively quickly; in contrast, when input was filtered through relatively large overlapping receptive fields, networks learned to encode specific shape exemplars or metric spatial relations relatively quickly. Moreover, when the receptive field sizes were allowed to adapt during learning, networks developed smaller receptive fields when they were trained to categorize shapes or spatial relations, and developed larger receptive fields when they were trained to encode specific exemplars or metric distances. In addition, when pairs of networks were constrained to use input from the same type of receptive fields, networks learned a task faster when they were paired with networks that were trained to perform a compatible type of task. Finally, using a novel modular architecture, networks were not preassigned a task, but rather competed to perform the different tasks. Networks with small nonover-lapping receptive fields tended to win the competition for categorical tasks whereas networks with large overlapping receptive fields tended to win the competition for exemplar/metric tasks.     

Experiences of Support Staff with Expanding and Strengthening Social Networks of People with Mild Intellectual Disabilities

A supportive social network is crucial for facilitating social inclusion. The social networks of people with intellectual disabilities (ID) are often small and typically include very little contact with friends and acquaintances who do not have ID. Professionals can play an important role in strengthening and expanding the social networks of clients. In this study, experiences with interventions aimed at doing this were examined. Six group interviews were held with a total of 27 professionals. The results showed interventions to strengthen social networks (e.g. attention to the maintenance of contact with network members) and interventions to expand social networks (e.g. participation in leisure time activities and working with volunteers). However, a large number of impeding factors was mentioned, such as the limited size of the social networks, characteristics of the client, different perceptions and clients falling between the cracks when it comes to leisure time. The large number of impeding factors shows the strengthening and expansion of social networks to be complicated in actual practice. Recommendations are thus made to strengthen and expand the social networks of clients in an innovative manner which also takes these impeding factors into account. Copyright © 2013 John Wiley & Sons, Ltd.