The Naming Game in social networks: community formation and consensus engineering

We study the dynamics of the Naming Game (Baronchelli et al. in J Stat Mech Theory Exp P06014, 2006b) in empirical social networks. This stylized agent-based model captures essential features of agreement dynamics in a network of autonomous agents, corresponding to the development of shared classification schemes in a network of artificial agents or opinion spreading and social dynamics in social networks. Our study focuses on the impact that communities in the underlying social graphs have on the outcome of the agreement process. We find that networks with strong community structure hinder the system from reaching global agreement; the evolution of the Naming Game in these networks maintains clusters of coexisting opinions indefinitely. Further, we investigate agent-based network strategies to facilitate convergence to global consensus.     

For the greater good: business networks and business social responsibility to communities

Business networks (co-operative arrangements between independent business organizations) may be the signature organizational form of the contemporary global economy. Many policy-makers and local leaders advocate business network membership as an alternative development strategy for regional economic vitality. The extant literature on business networks has focused on their association with business success. However, little is known about their impact on other aspects of community life. The purpose of this paper is to elaborate the role of network membership on one non-economic dimension of the business community interface. We examined the relationship between business network membership and business social responsibility to communities, defined as the provision of leadership and support for community betterment projects. Data were gathered from telephone interviews with a random sample of 460 non-metro small business operators in the USA. Independent t-tests and ordinary least squares regression analyses controlling for theoretically important variables were conducted. Findings show that networked businesses provide more leadership and support for their communities than non-networked businesses. However, networked businesses were no more likely than non-networked businesses to use local suppliers of goods and services.     

A dynamic perspective: local interactions driving the spread of social networks

ABSTRACT

This study takes a micro standpoint to quantitatively verify the extent to which local interactions affect the expansion of dynamic social networks. By reviewing and synthesizing the theoretical literature in this article, we seek to establish a pragmatic analytical framework to capture the underlying functioning of local interactions. It then aims to produce findings on seven distinct marketing campaigns in which the real-world virtual communities offer intact time-series connections. In our considered cases, the firm-to-consumer interactivity plays a pivotal role in social media marketing while the customer-driven influence advances individual information transmission. The significant positive relationships demonstrate features of interactivity within subgroups including reciprocal edges and directed 3-cliques associated with the evolution of the virtual community by electronic word-of-mouth (WOM) of both firm-to-consumer and consumer-to-consumer interactions. More importantly, the attenuation of local interactions to a large extent leads to the cut-off point of the growth of the dynamic social network.     

The Contingent Effects of Social Network Sparseness and Centrality on Managerial Innovativeness

Prior research has highlighted that network sparseness and network centrality enhance innovativeness through access to information and influence, respectively. We advance this perspective by exploring the extent to which individual actions are needed to mobilize information and influence accessed through social networks, and whether such information and influence would mutually reinforce to enhance managerial innovativeness. Our findings found partial support for the idea that actions are needed to actualize potential resources embedded in social networks, as centrally positioned managers enjoy higher innovativeness when they engage in ambassador activities. We also found that advice network sparseness and advice network centrality had independent, not interactive relationships with managerial innovativeness, suggesting that they offer distinct routes to achieving managerial innovativeness. Overall, our research clarifies the relationships of two important social network attributes on managerial innovativeness, and also sheds new light on how managerial action matters in realizing social network advantages for innovative ends.     

A qualitative analysis of cross-cultural new media research: SNS use in Asia and the West

The purpose of this paper is to examine the use of social network sites (SNSs) from a qualitative methodological approach, looking at both Asian and Western countries. There has been growing interest in systematic analysis of the use of SNSs as such sites have become increasingly popular, global means of self-expression and forming social connections. However, most previous research into SNSs has been based in a single cultural context, with very few cross-cultural studies having been conducted. To address this lacuna, this study compares SNS users in Korea with those in the United States, specifically examining the nature of their SNS social relationships and their attitudes toward self-disclosure via SNS. Using semi-structured focus interviews, our research provides qualitative data-based analysis of the culture-specific effects that new social media has on communication. Our study demonstrates that a qualitative method is useful when examining the cultural differences that appear in online communication behavior designed to establish social relationships and to compose content, and further indicates that cultural differences may have considerable influence on SNS users’ attitudes towards SNSs and on their communication style. This study thus contributes to existing literature by advancing the research into a broader, inter-cultural sphere.     

Inference of the Russian drug community from one of the largest social networks in the Russian Federation

The criminal nature of narcotics complicates the direct assessment of a drug community, while having a good understanding of the type of people drawn or currently using drugs is vital for finding effective intervening strategies. Especially for the Russian Federation this is of immediate concern given the dramatic increase it has seen in drug abuse since the fall of the Soviet Union in the early nineties. Using unique data from the Russian social network ‘LiveJournal’ with over 39 million registered users worldwide, we were able for the first time to identify the on-line drug community by context sensitive text mining of the users’ blogs using a dictionary of known drug-related official and ‘slang’ terminology. By comparing the interests of the users that most actively spread information on narcotics over the network with the interests of the individuals outside the on-line drug community, we found that the ‘average’ drug user in the Russian Federation is generally mostly interested in topics such as Russian rock, non-traditional medicine, UFOs, Buddhism, yoga and the occult. We identify three distinct scale-free sub-networks of users which can be uniquely classified as being either ‘infectious’, ‘susceptible’ or ‘immune’.     

Structural investigation of supply networks: A social network analysis approach

A system of interconnected buyers and suppliers is better modeled as a network than as a linear chain. In this paper we demonstrate how to use social network analysis to investigate the structural characteristics of supply networks. Our theoretical framework relates key social network analysis metrics to supply network constructs. We apply this framework to the three automotive supply networks reported in Choi and Hong (2002). Each of the supply networks is analyzed in terms of both materials flow and contractual relationships. We compare the social network analysis results with the case-based interpretations in Choi and Hong (2002) and conclude that our framework can both supplement and complement case-based analysis of supply networks.     

From network ties to network structures: Exponential Random Graph Models of interorganizational relations

Theoretical accounts of network ties between organizations emphasize the interdependence of individual intentions, opportunities, and actions embedded in local configurations of network ties. These accounts are at odds with empirical models based on assumptions of independence between network ties. As a result, the relation between models for network ties and the observed network structure of interorganizational fields is problematic. Using original fieldwork and data that we have collected on collaborative network ties within a regional community of hospital organizations we estimate newly developed specifications of Exponential Random Graph Models (ERGM) that help to narrow the gap between theories and empirical models of interorganizational networks. After controlling for the main factors known to affect partner selection decisions, full models in which local dependencies between network ties are appropriately specified outperform restricted models in which such dependencies are left unspecified and only controlled for statistically. We use computational methods to show that networks based on empirical estimates produced by models accounting for local network dependencies reproduce with accuracy salient features of the global network structure that was actually observed. We show that models based on assumptions of independence between network ties do not. The results of the study suggest that mechanisms behind the formation of network ties between organizations are local, but their specification and identification depends on an accurate characterization of network structure. We discuss the implications of this view for current research on interorganizational networks, communities, and fields.     

Classification of various attacks and their defence mechanism in online social networks: a survey

Due to the popularity and user friendliness of the Internet, numbers of users of online social networks (OSNs) and social media have grown significantly. However, globally utilised, social networks are the consequence of the lack of understanding of secrecy and protection on OSN and media has increased. Secrecy and surety of OSNs need to be inquired from various positions. According to recent studies, OSN users expose their private information such as email address, phone number etc. In this paper, we have presented a high-level classification of recent OSN attacks for recognising the problem and analysing the blow of such attacks on World Wide Web. We have also discussed OSN attacks on different social networking web applications by citing certain recent reports such as Kaspersky security network and Sophos security threat report. We also offer some simple-to-implement user practice tips to protect the system and user’s information. In addition to this, we have discussed a comprehensive analysis of numerous defensive approaches on OSN security. Lastly, based on the acknowledged strength and faults of these defensive approaches, we have explained open research issues.     

Precedence diagramming method: Some unusual characteristics and their implications for project managers

The Precedence Diagramming Method, with its activity-on-node network and additional precedence relationships, offers an easier and more flexible network approach to modeling large projects than conventional PERT/CPM. But the new relationships (start-to-start and finish-to-finish constraints) can change some of the basic notions of critical path methodology, including the concept of a critical path itself. Calculations of early and late job start times are affected, along with total slack. Traditional methods of shortening a project by crashing jobs on the critical path can occasionally have anomalous effects. These little-known characteristics of PDM are discussed, along with their implications for project managers, analysts, and other users of network methodology. Suggestions are made for improving the information available in computer printouts of PDM networks and for avoiding some of the anomalous effects. While PDM improves the project planner's ability to more simply and accurately model large projects, users should be aware of and able to effectively deal with its sometimes peculiar characteristics.     

Strategies affecting Twitter-based networking pattern of South Korean politicians: social network analysis and exponential random graph model

This paper examines the Twitter networking pattern of “following” and “mention” relationships between South Korean politicians. The data were obtained from the Twitter profiles of Korea’s national assemblymen and the most influential political figures. We conducted social network techniques including exponential random graph model and a regression method. The results suggest that these politicians employ two different strategies to establish relationships with other politicians on Twitter. One is “following” other politicians as a social ritual based on dyadic reciprocity, and the other is to “mention” other politicians as asymmetric political support based on the public popularity of their peers on Twitter.     

基于反向传播神经网络的煤矿建筑工程造价估算研究

人工神经网络通过模拟人脑或生物神经网络基本特性,具有较强的自组织和自学习能力,可以从大量的数据中提取内在规律,构造出自变量和因变量二者之间的映射关系,从而实现复杂非线性现象的有效模拟和预测。研究表明人工神经网络方法与其他方法相比在工程造价特征因素非线性和动态性描述方面具有潜在优势。     

Trade networks and economic fluctuations in Asian countries

The paper presents a new methodology, based on tensor decomposition, to map dynamic trade networks and to assess its strength in forecasting economic fluctuations at different periods of time in Asia. Using the monthly merchandise import and export data across 33 Asian economies, together with the US, EU and UK, we detect the community structure of the evolving network and we identify clusters and central nodes inside each of them. Our findings show that data are well represented by two communities, in which People's Republic of China and Japan play the major role. We then analyze the synchronisation between GDP growth and trade. Furthermore we apply our model to the prediction of economic fluctuations. Our findings show that the model leads to an increase in predictive accuracy, as higher order interactions between countries are taken into account.     

The structural,social, and strategic factors associated with successful business networks

Business networks, formal arrangements between independent businesses established to enhance member success, are generally accepted as an important strategy to help small businesses survive and prosper, and to promote regional economic development. However, knowledge about what contributes to the success of business networks themselves is less extensive and based primarily on case studies or reports of network directors. The purpose of this paper is to partially address this shortcoming. We consider the structural and social features identified in previous studies as likely correlates of business network success. Using a social constructionist definition of network success, we distinguish successful from less successful networks from among a sample of 29 industry and community business networks in the USA. Findings from interviews with 1122 members and 29 network leaders suggest that trust is central to understanding network success. Structural features have complex positive and negative indirect effects on success through trust and resource exchanges. The findings highlight the fact that business networks, while offering great potential as a way to enhance economic vitality of regions and industries, cannot be viewed as a simple remedy.     

Social networks,mass media and public opinions

Our opinions and ideas are shaped by what our friends said and what we read or watched on mass media. In this paper, we propose a concise and analyzable model to study the effects of mass media modeled as an applied external field, and social networks on public opinions based on the multi-state voter model, and a tuned parameter can control the relative intensity of the effects of mass media and social networks. We consider a generalized scenario where there exist committed or stubborn agents in the networks whose opinions are not affected by their friends or mass media. We find that the fraction of each opinion will converge to a value which only relates to the fractions and degrees of stubborn agents, and the relative intensity between media and network effects. The final agents with media opinion, except the stubborn agents, also include the increment produced by the internal impact of social networks and that caused by the external impact of media. Interestingly the second increment is composed of two parts, one is from the media effect when there are no interactions between agents and the other is from the influence of media on agent opinions caused by social network structure. That is the interactions among agents within social networks can amplify media influence. Finally we also discuss several extensions to the dynamics model which consider more realistic scenarios.     

Research on e-commerce transaction networks using multi-agent modelling and open application programming interface

We provide a formal definition of an e-commerce transaction network. Agent-based modelling is used to simulate e-commerce transaction networks. For real-world analysis, we studied the open application programming interfaces (APIs) from eBay and Taobao e-commerce websites and captured real transaction data. Pajek is used to visualise the agent relationships in the transaction network. We derived one-mode networks from the transaction network and analysed them using degree and betweenness centrality. Integrating multi-agent modelling, open APIs and social network analysis, we propose a new way to study large-scale e-commerce systems.     

The success and failure of policy-implanted inter-firm network initiatives: motivations,processes and structure

This paper examines the processes and causes of inter-firm network success and failure, defined in terms of the ability of networks to become a sustained and valued form of business activity for their members. The paper examines four different case study network initiatives: (1) a failed informal ‘new entrepreneurs' network’ (2) a successful informal ‘local cluster group’ (3) a failed formal ‘defence contractors' network’ and (4) a successful formal ‘small-firm technology group’. It is shown that networks in business are often consciously developed and maintained by those managing directors who have recognized the importance of cooperative activities for achieving competitive advantage for their companies. The best network support consisted of brokers who are able to mix and overlap the ‘hard’ business and ‘softer’ social interests of participants. The case studies indicate that it is formal groups that are the most potent form of inter-firm network, but that it is through an initially informal structure that they are best facilitated. It is concluded that both economic and social rationalities are at play in the motivation of firms to join networks, and that their success is closely connected to pre-existing commonality between members.     

Networks to Nerdistan: The Role of Labor Market Intermediaries in the Entry‐level IT Labor Market

Although networks have long governed economic relations, they assume even more importance in a knowledge‐based economy. Yet, some argue that because of the lack of social networks and human capital, some groups are permanently ‘switched off’ the networks of the global economy. Evidence presented in this article suggests that instead there is latent potential for access to the network, due to the rise of networked community‐based organizations and the increasing accessibility of technology. Based on surveys and in‐depth interviews with almost 700 workers and training providers, I show how the switched off are entering jobs in information technology through network ties and the acquisition of soft skills, or communication and interaction skills. Although community‐based training providers are best positioned to help disadvantaged jobseekers enter the network society, changes in the US workforce development system are reinforcing network exclusivity, rather than facilitating this upward mobility.     

社交网络数据的分析及可视化技术

随着企业信息化的发展,数据可视化在社交网站上扮演着越来越重要的角色。数据可视化技术以更直观的方式表现数据及其结构关系,帮助用户理解大量的数据信息,发现数据中隐含的现象,提高数据的使用效率。对Java,SVG,ADOBE FLEX三种常用的可视化展示方法进行研究,比较分析其优缺点,并着重说明了ADOBE FLEX运用与社交网站!