Search in Power-Law Networks

Many communication and social networks have power-law link distributions, containing a few nodes which have a very high degree and many with low degree. The high connectivity nodes play the important role of hubs in communication and networking, a fact which can be exploited when designing efficient search algorithms. We introduce a number of local search strategies which utilize high degree nodes in power-law graphs and which have costs which scale sub-linearly with the size of the graph. We also demonstrate the utility of these strategies on the Gnutella peer-to-peer network.Comment: 17 pages, 14 figure

Sharing Social Network Data: Differentially Private Estimation of Exponential-Family Random Graph Models

Motivated by a real-life problem of sharing social network data that contain sensitive personal information, we propose a novel approach to release and analyze synthetic graphs in order to protect privacy of individual relationships captured by the social network while maintaining the validity of statistical results. A case study using a version of the Enron e-mail corpus dataset demonstrates the application and usefulness of the proposed techniques in solving the challenging problem of maintaining privacy \emph{and} supporting open access to network data to ensure reproducibility of existing studies and discovering new scientific insights that can be obtained by analyzing such data. We use a simple yet effective randomized response mechanism to generate synthetic networks under $\epsilon$-edge differential privacy, and then use likelihood based inference for missing data and Markov chain Monte Carlo techniques to fit exponential-family random graph models to the generated synthetic networks.Comment: Updated, 39 page

Integrating personal learning and working environments

This review paper part of a series of papers commissioned by the Institute for Employment Research at the University of Warwick under the title of 'Beyond Current Horizons – Working and Employment Challenge'. In turn, in forms part of a larger programme of work under the banner of Beyond Current Horizons that is being managed by FutureLab on behalf of the UK Department for Schools, Children and Families. The brief was to cover: - The main trends and issues in the area concerned; - Any possible discontinuities looking forward to 2025 and beyond; - Uncertainties and any big tensions; - Conclusions on what the key issues will be in the future and initial reflections on any general implications for education. Given the wide ranging nature of the brief, this paper largely confines itself to trends and issues in the UK, although where appropriate examples from other countries in Europe are introduced. We realise that in an age of growing globalisation the future of work and learning in the UK cannot be separated from developments elsewhere and that developments in other parts of the world may present a different momentum and trajectory from that in the UK. Thus, when reading this report, please bear in mind the limitations in our approach