Networks, or graphs, are pervasive in our modern society. A network consists of entities, or nodes, and a set of relationships between those entities, or edges. When we consider social media services (Facebook, Twitter, etc), nodes correspond to user accounts and edges would be friendships between these users. Nodes often have information associated with them, or attributes. In a social network, these attributes could be as simple as demographic data or information that a particular user has at a given time. In an intelligent infrastructure setting, where nodes and edges correspond to a road network, the level of congestion along stretches of road would be an attribute of the network. In general, networks that have attributes associated with their nodes and edges are called multivariate networks and are an emerging area of information visualisation. Multivariate networks can also be dynamic. That is, either the structure of the network itself or the attributes associated with the nodes and edges can change over time. In a social network setting, friendships are formed and are broken, evolving the network. Information that a friend might have can spread from node to node cascading through the network structure. In a city, new roadways can be built or closed, corresponding to structural changes in the network. Levels of congestion vary throughout the course of the day and therefore the attributes can change as well. Networks where the structure and/or attributes change over time are dynamic multivariate networks and understanding how they operate is critical for these applications and many others. In information visualisation, this emerging area has received much recent attention. The challenge of this work occurs when the network structure and/or the attributes change over time and we would like to visualise these changes effectively. As many networks, particularly social networks, do not have inherent spatial positions for the nodes, we are free to choose these positions. Also, we are free to choose the encodings for the attributes. However, we must do so in a way that is both computationally efficient and perceptually effective for the end user of the visualisation. In this work, we look at perceptually effective ways for drawing and visualising dynamic multivariate graphs. We work closely with research scientists at the Oxford Internet Institute to ensure impact on software that is already in use with various user communities. For this work, we are inspired by studies in psychology and perception in order to drive the design of algorithms to draw the graph and interactive methods for their visualisation. We concentrate on methods for drawing and visualising both evolving structure and evolving attributes. In order to ensure our algorithms conform to the desired perceptual criteria, we evaluate our computational processes through metric evaluations and evaluate our visualisations through user centred experimentation. By working closely with our collaborators in social networks, we ensure the work is relevant for analysing social networks.

This project aims to explore the contribution of digitally mediated labour to the provision of decent work and livelihoods among displaced persons in cities, with a focus on Berlin and Beirut. Both these cities are leading hubs for digital innovation and have recently absorbed large numbers of refugees, prompting a growth in digital work initiatives. These emerged against the backdrop of a growing online 'gig economy' around the world amid an increasingly urban and 'connected' displaced population: more than 60 percent of the world's refugees now live in cities. These combined factors of urbanised refugee economies and the digitalisation of work demand urgent research into the relationship between the online gig economy and displaced populations. Yet despite a growing body of research on digital economies in development contexts, it is poorly understood how the online gig economy reshapes the world of work among displaced persons. Aiming to fill this knowledge gap in partnership with the International Labour Organization (ILO), the Oxford Internet Institute (OII), and hosted by the University of Edinburgh, this project pursues three research objectives: a) Generate empirical evidence about the digitally mediated work lives of refugees through fieldwork in Berlin and Beirut; b) Gain insights through research of selected digital platforms that offer digital work opportunities and employment trainings; c) Establish a new methodological framework that links ethnography with multidisciplinary methods in the social sciences of the digital, and develop new research skills through trainings. In fulfilment of these research objectives, the project follows two overarching questions: 1) How does digitally mediated labour reshape refugees' access to decent work and sustainable livelihoods? 2) What implications do these transformations have for the rights and policies that govern urban refugee economies, and for the way displacement is conceptualised in the social sciences? These overarching questions are complemented by three empirical sub-questions that correspond directly to the research objectives and three methodological dimensions: a) What types of digitally mediated work do refugees do, how do they get access to it, and what impact does it have on their social and economic lives? b) How do digital work platforms relate to the specific situation of displaced populations, and what impact do they pursue in comparison to the actual experiences of refugee workers? c) What new combinations of qualitative ethnographic research and digital research methods allow us to grasp how digital economies and refugees' working practices intersect and overlap? In line with the New Investigator Grant's aims, the project pursues additional objectives on two levels: skills development and impact. Skills development objectives include completion of a leadership programme at the host institution; the development of new approaches and methods during a three-months visit to the Oxford Internet Institute (OII); and the learning of effective user engagement by collaborating with the ILO and providers of digital work opportunities in the third sector and the private sector. The knowledge exchange and impact objectives include convening a workshop and an international conference with key users at the host institution; production of high-quality research outputs, including an ILO Working Paper, with impact on both users and academic beneficiaries; the creation of a project website and a Briefing for policy makers and platform developers titled 'A Just Gig Economy for Refugees'. The newly gained skills, networks and knowledge throughout this project will facilitate the creation of sustainable research capacity at the host institution through follow-up funding applications with a clear long-term aim in mind: the formation of a research cluster on 'Digital Development' at Edinburgh's School of Social and Political Science.

When you plug your fridge into the mains electricity supply you don't worry about all the technology sitting behind the wall socket -- it just works. Cloud computing is starting to supply IT in a similar fashion. No more worrying about backups, no more hours spent configuring a new or repaired machine -- just plug into the network, fire up your web browser and away you go.Researchers have tougher and more specialised IT needs than most, so to realise the same ease of use that the cloud now provides for email or word processing requires work in several areas. One of these areas is to adapt existing established research tools to the cloud, and that is what this project will do. Our tool is called GATE, a General Architecture for Text Engineering. Over the last decade the UK's GATE system has become a world-leader for research and development of text mining algorithms.Text has become a more and more important communication method in recent decades. Our children are now spending over 6 hours in front of screens; our evenings often include sessions on Facebook or writing email to friends and relatives. When we interact with the corporations and governmental organisations whose infrastructure and services underpin our daily lives, we fill in forms or write emails. When we want to publicise our work or share details of our leisure activities we create websites, post Twitter messages or blog entries. Scientists also now use these channels in their work, in addition to publishing in peer-reviewed journals -- a process which has also seen a huge expansion in recent years.This avalanche of the written word has changed many things, not least the way that scientists gather information. For example, a team at the World Health Organisation's cancer research agency recently found the first evidence of a link between particular genetic mutation and the risk of lung cancer in smokers. Their experiments require large amounts of costly laboratory time to test hypotheses, based on samples of mutations in gene sequences from their test subjects. Text mining from previous publications makes it possible for them to reduce this lab time by factoring in probabilities based on association strengths between mutations, environmental factors and active chemicals.A second area that has been revolutionised by new media is customer relations and market research, which are no longer about monitoring the goings on of the corporate call centre. Keeping up to date with the public image of your products or services now means coping with the Twitter firehose (45 million posts per day), the comment sections of consumer review sites, or the point-and-click 'contact us' forms from the company website. To do this by hand is now impossible in the general case: the data volume long ago outstripped the possibility of cost-effective manual monitoring. Text mining provides alternative, automatic methods for dealing with text.GATE provides four systems to support scientists experimenting with new text mining algorithms and developers using text mining in their applications:- GATE Developer: an integrated development environment for language processing components- GATE Embedded: an object library optimised for inclusion in diverse applications- GATE Teamware: a collaborative annotation environment for high volume web-based semantic annotation projects built around a workflow engine- GATE Mmir: (Multi-paradigm Information Management Index and Repository) a massively scaleable multi-paradigm indexWe have identified a need for a particular type of cloud service in our research field and this project will implement it such that there is close to zero barrier to entry for researchers. Based on our preliminary investigative work, we expect to complete a production quality service within this project. In simpler terms - this project will work towards making use of GATE on the cloud more like electric sockets and fridges!

The success of Web 2.0 and CGM is based on tapping into the social nature of human interactions, by making it possible for people to voice their opinion, become part of a virtual community and collaborate remotely. If we take micro-blogging as an example, the growth in Twitter visits between 2008 and 2009 was over 1,000% and it is projected that by 2010 around 10% of all internet users will be on Twitter. This unprecedented rise in the volume and importance of online content has resulted in companies and individuals spending ever increasing amounts of time trying to keep up with relevant CGM. It is estimated that 700 person hours per year is the absolute minimum that companies and public services need to spend on CGM monitoring, online user engagement, and discovery of new information. This fellowship is about helping people to cope with the resulting information overload, through automatic methods that are capable of adapting to individual's information seeking goals and summarising briefly the relevant media and thus supporting information interpretation and decision making. Automatic text summarisation is key to our goal and consists of compressing the meaning of text documents while preserving the relevant information contained within them. While there has been a lot of research on well-authored texts such as news, summarisation of social media is still in its infancy, with research focused on product reviews. A key experimental finding has been that due to the characteristics of social media (product reviews in particular) it is better first to abstract the relevant information from the different documents and sites and then to use natural language generation to create a fluent text based on this information.In this fellowship I will investigate and evaluate new machine learning methods for personalised, abstractive multi-document summarisation across different social media. For example, diachronic summaries that combine Twitter posts, blog articles, and Facebook wall messages on a given topic. In contrast to previous work, we will pursue an inter-disciplinary approach, which will help us study the social dimension of CGM summarisation and establish actual user needs. The second research challenge is that the algorithms need to be robust in the face of this noisy, jargon-full and dynamic content, as well as needing models capable of representing the contradictory and strongly temporal nature of CGM. A key novel contribution of our work is personalising the summaries, based on a model of user interests, goals, and social context. Issues such as trustworthiness, privacy, and online communities (with their hubs and authorities) will also play an important role. The fourth research challenge is to generate personalised abstractive summaries that can help users with sensemaking and content interpretation. An exciting element of my research will be in studying the different kinds of summaries that are useful for a variety of real users (companies, journalists, and the general public) through multi-disciplinary collaborations with the Press Association, British Telecom, the Oxford Internet Institute, and Sheffield's Department of Journalism. A key project deliverable will be a publicly available browser plugin that provides easy access to the automatically generated summaries. This will allow me to evaluate the project results with real users, on a large scale. It will also provide a new evaluation challenge for the Natural Language Generation community, as researchers will be able to compare their summarisers against those delivered by our open-source algorithms. Last but not least, the fellowship covers not only foundational multi-disciplinary research but it also tests the results in several Digital Economy pilot experiments involving commercial partners (The Press Association, British Telecom, Fizzback).