公正的网络道德审判是否可能?——基于旁观者视角

网络道德审判是对传统道德审判的继承与发展,存在着显著的伦理困境：它理应通过激发正向羞耻感来促进对行为者的伦理教化,但在诸多情况中却因引发负向羞耻感而产生对行为者的伦理排斥。网络道德审判作为一种典型的道德评价形态,可以利用情感主义伦理学中的旁观者视角来加以考察。据此可发现,网络旁观者的同情、想象、事实判断能力存在着诸多困境,同时其群体性特征又进一步加剧了潜在的风险。实现公正的网络道德审判,需要汲取和借鉴“公正的旁观者”的多重意蕴来构建可能的伦理进路。     

农业对外投资布局对母国参与全球价值链的影响——基于社会网络分析视角

参与全球农业价值链,是保障国家粮食安全、提高农业产业竞争力和影响力的重要举措。基于TiVA数据库和UN COMTRADE数据库测算64个国家全球农业价值链的参与程度与分工地位,采用社会网络分析方法构建全球农业对外投资网络,实证分析农业对外投资布局对一国参与全球农业价值链的影响。结果表明,当前全球农业对外投资网络由发达国家主导;网络中心性和网络异质性对全球价值链地位有显著正向影响,即一国越处于网络中心且投资金额越分散,其价值链地位越高;网络规模有负向影响,盲目拓展投资网络的规模化优势难以抵消农业对外投资的高风险。基于研究结果,从分环节优化农业对外投资布局、深耕既有农业对外投资网络、逐步嵌入发达国家主导的农业对外投资网络等方面提出促进中国价值链地位攀升的建议。     

医药企业负面网络舆情演化及应对策略研究

探讨因媒体不当报道引发医药企业网络舆情危机的演变规律,为企业找寻适宜的对策,有助于提高医药企业危机应对能力。文章以“深圳康泰公司乙肝疫苗信任危机”为例,构建了医药企业负面网络舆情演化和响应策略的系统动力学模型,并采用Vensim PLE软件进行仿真。结果表明:医药企业负面网络舆情经过酝酿、爆发、衰退三个阶段,且呈现爆发时间短、热度高、负面情绪强的特点;医药企业应根据舆情演化阶段特征采取不同应对策略,三个阶段对应有效应急策略依次是提升舆情监测能力、端正担责态度、提高信息公开度和沟通能力、注意形象修复和注重人文关怀。其中,提高信息公开度和沟通能力对负面网络舆情热度的峰值均有明显的削弱效果,整体提升企业舆情应对能力是改善舆情、挽救医药行业信任危机的有力措施。     

Modular-transform based clustering

Spectral clustering uses eigenvectors of the Laplacian of the similarity matrix. It is convenient to solve binary clustering problems. When applied to multi-way clustering, either the binary spectral clustering is recursively applied or an embedding to spectral space is done and some other methods, such as K-means clustering, are used to cluster the points. Here we propose and study a K-way clustering algorithm – spectral modular transformation, based on the fact that the graph Laplacian has an equivalent representation, which has a diagonal modular structure. The method first transforms the original similarity matrix into a new one, which is nearly disconnected and reveals a cluster structure clearly, then we apply linearized cluster assignment algorithm to split the clusters. In this way, we can find some samples for each cluster recursively using the divide and conquer method. To get the overall clustering results, we apply the cluster assignment obtained in the previous step as the initialization of multiplicative update method for spectral clustering. Examples show that our method outperforms spectral clustering using other initializations.     

Discrete Multicolour Random Mosaics with an Application to Network Extraction

We introduce a class of random fields that can be understood as discrete versions of multicolour polygonal fields built on regular linear tessellations. We focus first on a subclass of consistent polygonal fields, for which we show Markovianity and solvability by means of a dynamic representation. This representation is used to design new sampling techniques for Gibbsian modifications of such fields, a class which covers lattice‐based random fields. A flux‐based modification is applied to the extraction of the field tracks network from a Synthetic Aperture Radar image of a rural area.     

The roles of supply network centralities in firm performance and the moderating effects of reputation and export-orientation

Abstract

This study explores how supply network degree, closeness, and betweenness centralities affect firm performance, and the moderating effects of organizational reputation (measured by PageRank centrality) and export-orientation. The supply chain relationship empirical data are drawn from manufacturing and manufacturing service companies in Hong Kong, China. Social network analysis and moderated regression analysis were adopted to test the hypotheses for a sample of 814 focal firms with 3086 supply chain ties. The results indicate that in-degree and closeness centralities improve firm performance. Reputation is found to positively moderate the relationship between closeness and sales performance, but negatively moderates the relationship between betweenness and sales performance. Export-orientation has no effect on relationships. This study contributes to the literature by providing additional empirical evidence on the role of supply network position in firm performance. It also introduces PageRank centrality as a new measure of organizational reputation in a supply network.     

Understanding labour processes in global production networks: a case study of the football industry in Pakistan

ABSTRACT

Over the last few decades, the changing nature of global production and distribution processes has raised a number of critical questions regarding work and employment relations. Presenting a qualitative case study of the football industry in Pakistan as an example of the general mechanism of the social relations of re/production in a global system of industrial organization, this research highlights how and under what conditions informal workers are embedded in extended global production networks. By drawing on the integrated conceptual framework of the global production network (GPN) and labour process theory (LPT), this research sheds light on the working conditions and living realities of informal workers. A potential contribution of this paper is to extend the horizon of production network theory by analysing the work and employment conditions of informal workers, which are absent in existing discussions of these conceptual frameworks.     

PCA likelihood ratio test approach for attributed social networks monitoring

Abstract

One of the most important factors in building and changing communication mechanisms in social networks is considering features of the members of social networks. Most of the existing methods in network monitoring don’t consider effects of features in network formation mechanisms and others don’t lead to reliable results when the features abound or when there are correlations among them. In this article, we combined two methods principal component analysis (PCA) and likelihood method to monitor the underlying network model when the features of individuals abound and when some of them have high correlations with each other.     

A novel approach based on multiple correspondence analysis for monitoring social networks with categorical attributed data

In in most cases, the distribution of communications is unknown and one may summarize social network communications with categorical attributes in a contingency table. Due to the categorical nature of the data and a large number of features, there are many parameters to be considered and estimated in the model. Hence, the accuracy of estimators decreases. To overcome the problem of high dimensionality and unknown communications distribution, multiple correspondence analysis is used to reduce the number of parameters. Then the rescaled data are studied in a Dirichlet model in which the parameters should be estimated. Moreover, two control charts, Hotelling’s T² and multivariate exponentially weighted moving average (MEWMA), are developed to monitor the parameters of the Dirichlet distribution. The performance of the proposed method is evaluated through simulation studies in terms of average run length criterion. Finally, the proposed method is applied to a real case.     

国内网络素养领域的研究现状——基于CNKI数据库的文献计量分析

以中国知网CNKI期刊数据库为数据来源,采用文献计量方法对国内网络素养的研究现状进行分析发现：目前国内网络素养研究的文献增长符合指数增长规律,正处于知识积累的发展阶段;该研究领域为多学科交叉领域,教育学、马克思主义学、新闻学与传播学是其研究的核心阵地;目前核心作者群还比较薄弱,固定的科研合作团队较少;大学生及青少年（包括未成年人）是该领域的主要研究对象,新媒体、网络舆情、网络行为、网络理性、网络道德等是该领域的研究热点。