Nowcasting with Google Trends : a keyword selection method

Search engines, such as Google, keep a log of searches entered into their websites. Google makes this data publicly available with Google Trends in the form of aggregate weekly search term volume. Aggregate search volume has been shown to be able to nowcast (i.e. compute real-time assessment of current activity) a variety of variables such as influenza outbreaks, financial market fluctuations, unemployment and retail sales. Although identifying appropriate keywords in Google Trends is an essential element of using search data, the recurring difficulty identified in the literature is the lack of a technique to do so. Given this, the main goal of this paper is to put forward a method (the "backward induction method") of identifying and extracting keywords from Google Trends relevant to economic variables

Candor & Ebb: Searching For My Truth Through Solo Performance

This thesis is an examination of autobiographical solo performance. It explores the use of personal trauma and illness in the dramatic form. In addition to investigating how other solo performing artists utilize their medical conditions in their work, this thesis gives some historical context to the author’s own process and development. The thesis culminates in the author’s solo performance script and a desire for its audience to find solace and compassion through the experience of witnessing it being performed

Regional Determinants of Entrepreneurship in a Small Economy: Panel Data Evidence from Scotland.

This paper analyses the spatial variation of new entrepreneurial activity across 32 Scottish regions for the period 1998-2007. Entrepreneurship is widely recognised as a key determinant of economic growth, regional prosperity and sustainable development. Using data from the Value Added Tax (VAT) register, this paper estimates spatial variation in new entrepreneurial activity using a panel data model. Results show that there is considerable variation in entrepreneurship across Scottish regions and that this variation may be explained by demand and supply factors, policy and cultural factors and agglomeration benefits. Given that Scotland has recently suffered from low levels of entrepreneurship compared with other parts of the UK and similar sized smaller countries, this paper provides relevant and timely findings, as Scotland attempts to recover from the recent recession.

"Nourishing European Interest Groups: The Delors Commission and Labour"

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Audit and Certification of Digital Repositories: Creating a Mandate for the Digital Curation Centre (DCC)

The article examines the issues surrounding the audit and certification of digital repositories in light of the work that the RLG/NARA Task Force did to draw up guidelines and the need for these guidelines to be validated.

The Role of Evidence in Establishing Trust in Repositories

This article arises from work by the Digital Curation Centre (DCC) Working Group examining mechanisms to roll out audit and certification services for digital repositories in the United Kingdom. Our attempt to develop a program for applying audit and certification processes and tools took as its starting point the RLG-NARA Audit Checklist for Certifying Digital Repositories. Our intention was to appraise critically the checklist and conceive a means of applying its mechanics within a diverse range of repository environments. We were struck by the realization that while a great deal of effort has been invested in determining the characteristics of a 'trusted digital repository', far less effort has concentrated on the ways in which the presence of the attributes can be demonstrated and their qualities measured. With this in mind we sought to explore the role of evidence within the certification process, and to identify examples of the types of evidence (e.g., documentary, observational, and testimonial) that might be desirable during the course of a repository audit.

Computation of epidemic final size distributions

We develop a new methodology for the efficient computation of epidemic final size distributions for a broad class of Markovian models. We exploit a particular representation of the stochastic epidemic process to derive a method which is both computationally efficient and numerically stable. The algorithms we present are also physically transparent and so allow us to extend this method from the basic SIR model to a model with a phase-type infectious period and another with waning immunity. The underlying theory is applicable to many Markovian models where we wish to efficiently calculate hitting probabilities.Comment: final published versio