Policy in the knowledge economy social network : a social capital redux

Purpose – The purpose of this paper is to suggest how enabling policy should be focused in a knowledge economy by developing the concept of a knowledge economy social network (KESN).

Design/methodology/approach – The paper employs an interdisciplinary approach in developing the KESN by drawing on concepts and methodology from economics, political science and social network theory.

Findings – The KESN's social capital is defined. As such, maintaining accountability, increasing cohesion and connections among knowledge actors are suggested as relevant guidelines for policy in the KESN.

Research limitations/implications – The knowledge economy should ideally be seen as having unique needs compared to the traditional economy in devising policy.

Practical implications – The paper suggests using the KESN as a basis for devising policy for a knowledge economy.

Originality/value – The paper uses an interdisciplinary approach to studying the knowledge economy and introduces the KESN.

Influence of social network structure on entrepreneurship participation — a study of 20 national

By investigating differences in social networks among entrepreneurs in 20 cultures, this paper contributes to the debate on whether there is universality in the process of entrepreneurial networking. Representative samples of entrepreneurs were identified in the same manner in 20 countries from 2000 to 2004 (N=€‰304,560). The sampling methodologies and the questions asked were similar across all countries. Logistic regression was used to test for significant regional interaction effects involving personally knowing an entrepreneur. Results are contrary to the existence of any mono-dimensional form of networking practice but do strongly support the existence of both variform universality (culture moderates the importance of networking) and functional universality (cultural similarities in networking practice exist).

Who will be an entrepreneur? How cultural mechanisms and social network structure together influence entrepreneurial participation

Using data collected from 35 countries over five years, this study provides an investigation of the combined influence of cultural factors and social network structure on whether or not an individual, anywhere in the world, becomes an entrepreneur. Results show that knowing someone who has started a business recently, across the world, has a significant impact on entrepreneurship participation. Regarding the potential cultural influences, it seems that importance attached to personally knowing entrepreneurs differs significantly between individuals operating in different cultures. In cultures with high power distance, personally knowing a person who recently started a business is relatively less important as a driver of entrepreneurship participation compared to cultures with low power distance. On the other hand, in cultures where the Hofstede’s ‘masculinity’construct predominates, it is more important than in cultures characterised by ‘femininity’.

The application of social network analysis to team sports

This article reviews how current social network analysis might be used to investigate individual and group behavior in sporting teams. Social network analysis methods permit researchers to explore social relations between team members and their individual-level qualities simultaneously. As such, social network analysis can be seen as augmenting existing approaches for the examination of intra-group relations among teams and provide detail of team members' informal connections to others within the team. Social network analysis is useful in addressing the issue of interdependencies in the data inherent in team structures. Social network terms are introduced and explained by way of an example team, software and resources are discussed, and a statistical approach to social network analysis is introduced.

OST : A transaction based online social trust model for social network and file sharing security

The continuous growth of the users pool of Social Networking web sites such as Facebook and MySpace, and their incessant augmentation of services and capabilities will in the future, meet and compare in contrast with today's Content distribution Networks (CDN) and Peer-to-Peer File sharing applications such as Kazaa and BitTorrent, but how can these two main streams applications, that already encounter their own security problems cope with the combined issues, trust for Social Networks, content and index poisoning in CDN? We will address the problems of Social Trust and File Sharing with an overlay level of trust model based on social activity and transactions, this can be an answer to enable users to increase the reliability of their online social life and also enhance the content distribution and create a better file sharing example. The aim of this research is to lower the risk of malicious activity on a given Social Network by applying a correlated trust model, to guarantee the validity of someone's identity, privacy and trustfulness in sharing content.

A social network analysis model for analysing stakeholder-associated safety risks in infrastructure projects

An important strategy in the long-term blueprint for making Australia's 18 capital and major regional cities more productive, sustainable and liveable is to develop high quality public infrastructure systems to improve civic quality of life. Because of the unique features of construction activities, such as long period, complicated processes, and dynamic organizational structures, infrastructure projects normally involve multiple stakeholders and are subject to various risks, especially safety issues. Any negligence or mismanagement of critical safety risks will have huge impact on achieving project objectives and success. Although many previous studies have identified and assessed various safety risks in construction industry, a main research gap is that these studies ignored a fact that most risks are interrelated and associated with internal and external stakeholders of the projects. The lack of a theoretical foundation and appropriate methods for analysing stakeholder-associated safety risks and their interdependencies in infrastructure projects hinders effective risk management processes and the formulations of decision strategies. This research aims at enabling higher performance in strategic safety risk management in infrastructure projects through the development of a holistic risk analysis model using Stakeholder and Social Network Theories. The outcomes can broaden project managers' awareness of emerging influential safety risks and enhance their ability to perceive, understand, assess, and mitigate safety risks in an effective and efficient way; thereby higher performance in strategic risk management could be achieved in infrastructure projects.

Stakeholder analysis in urban development : the application of stakeholder circle methodology and social network analysis

The increasing research interest on stakeholder analysis in urban planning reflects a growing recognition that stakeholders can and should influence the decision-making. This paper concentrates on exploring the techniques for analysing stakeholders, especially the application of the Stakeholder Circle tool and Social Network Analysis. An urban renewal project and an infrastructure project in Australia are presented as case studies to verify the use of these two techniques. The stakeholders are identified and prioritized from two different points of view, namely, the attribute evaluations in the Stakeholder Circle tool, and the relationship network analysis. The paper ends with a discussion on the strengths and limitations of the techniques for stakeholder analysis. No method for stakeholder identification and prioritization is perfect. The selection of the approaches is an art with extensive considerations of ‘when, what, and how’ to choose methods to achieve the project objectives. Each method has its own strengths and limitations. Combining several methods when necessary is the best way to analyse stakeholders.

Attack vector analysis and privacy-preserving social network data publishing

This paper addresses the problem of privacy-preserving data publishing for social network. Research on protecting the privacy of individuals and the confidentiality of data in social network has recently been receiving increasing attention. Privacy is an important issue when one wants to make use of data that involves individuals' sensitive information, especially in a time when data collection is becoming easier and sophisticated data mining techniques are becoming more efficient. In this paper, we discuss various privacy attack vectors on social networks. We present algorithms that sanitize data to make it safe for release while preserving useful information, and discuss ways of analyzing the sanitized data. This study provides a summary of the current state-of-the-art, based on which we expect to see advances in social networks data publishing for years to come.

Privacy threat analysis of social network data

Social network data has been increasingly made publicly available and analyzed in a wide spectrum of application domains. The practice of publishing social network data has brought privacy concerns to the front. Serious concerns on privacy protection in social networks have been raised in recent years. Realization of the promise of social networks data requires addressing these concerns. This paper considers the privacy disclosure in social network data publishing. In this paper, we present a systematic analysis of the various risks to privacy in publishing of social network data. We identify various attacks that can be used to reveal private information from social network data. This information is useful for developing practical countermeasures against the privacy attacks.

The social network virtual design studio : integrated design learning using blended learning environments

Online communications, multimedia, mobile computing and face-to-face learning create blended learning environments to which some Virtual Design Studios (VDS) have reacted to. Social Networks (SN), as instruments for communication, have provided a potentially fruitful operative base for VDS. These technologies transfer communication, leadership, democratic interaction, teamwork, social engagement and responsibility away from the design tutors to the participants. The implementation of Social Network VDS (SNVDS) moved the VDS beyond its conventional realm and enabled students to develop architectural design that is embedded into a community of learners and expertise both online and offline. Problem-based learning (PBL) becomes an iterative and reflexive process facilitating deep learning. The paper discusses details of the SNVDS, its pedagogical implications to PBL, and presents how the SNVDS is successful in enabling architectural students to collaborate and communicate design proposals that integrate a variety of skills, deep learning, knowledge and construction with a rich learning experience.