Trust and Privacy Permissions for an Ambient World

Ambient intelligence (AmI) and ubiquitous computing allow us to consider a future where computation is embedded into our daily social lives. This vision raises its own important questions and augments the need to understand how people will trust such systems and at the same time achieve and maintain privacy. As a result, we have recently conducted a wide reaching study of people’s attitudes to potential AmI scenarios with a view to eliciting their privacy concerns. This chapter describes recent research related to privacy and trust with regard to ambient technology. The method used in the study is described and findings discussed

From Social Data Mining to Forecasting Socio-Economic Crisis

Socio-economic data mining has a great potential in terms of gaining a better understanding of problems that our economy and society are facing, such as financial instability, shortages of resources, or conflicts. Without large-scale data mining, progress in these areas seems hard or impossible. Therefore, a suitable, distributed data mining infrastructure and research centers should be built in Europe. It also appears appropriate to build a network of Crisis Observatories. They can be imagined as laboratories devoted to the gathering and processing of enormous volumes of data on both natural systems such as the Earth and its ecosystem, as well as on human techno-socio-economic systems, so as to gain early warnings of impending events. Reality mining provides the chance to adapt more quickly and more accurately to changing situations. Further opportunities arise by individually customized services, which however should be provided in a privacy-respecting way. This requires the development of novel ICT (such as a self- organizing Web), but most likely new legal regulations and suitable institutions as well. As long as such regulations are lacking on a world-wide scale, it is in the public interest that scientists explore what can be done with the huge data available. Big data do have the potential to change or even threaten democratic societies. The same applies to sudden and large-scale failures of ICT systems. Therefore, dealing with data must be done with a large degree of responsibility and care. Self-interests of individuals, companies or institutions have limits, where the public interest is affected, and public interest is not a sufficient justification to violate human rights of individuals. Privacy is a high good, as confidentiality is, and damaging it would have serious side effects for society.Comment: 65 pages, 1 figure, Visioneer White Paper, see http://www.visioneer.ethz.c

When Social Influence Meets Item Inference

Research issues and data mining techniques for product recommendation and viral marketing have been widely studied. Existing works on seed selection in social networks do not take into account the effect of product recommendations in e-commerce stores. In this paper, we investigate the seed selection problem for viral marketing that considers both effects of social influence and item inference (for product recommendation). We develop a new model, Social Item Graph (SIG), that captures both effects in form of hyperedges. Accordingly, we formulate a seed selection problem, called Social Item Maximization Problem (SIMP), and prove the hardness of SIMP. We design an efficient algorithm with performance guarantee, called Hyperedge-Aware Greedy (HAG), for SIMP and develop a new index structure, called SIG-index, to accelerate the computation of diffusion process in HAG. Moreover, to construct realistic SIG models for SIMP, we develop a statistical inference based framework to learn the weights of hyperedges from data. Finally, we perform a comprehensive evaluation on our proposals with various baselines. Experimental result validates our ideas and demonstrates the effectiveness and efficiency of the proposed model and algorithms over baselines.Comment: 12 page

Amplifying Quiet Voices: Challenges and Opportunities for Participatory Design at an Urban Scale

Many Smart City projects are beginning to consider the role of citizens. However, current methods for engaging urban populations in participatory design activities are somewhat limited. In this paper, we describe an approach taken to empower socially disadvantaged citizens, using a variety of both social and technological tools, in a smart city project. Through analysing the nature of citizens’ concerns and proposed solutions, we explore the benefits of our approach, arguing that engaging citizens can uncover hyper-local concerns that provide a foundation for finding solutions to address citizen concerns. By reflecting on our approach, we identify four key challenges to utilising participatory design at an urban scale; balancing scale with the personal, who has control of the process, who is participating and integrating citizen-led work with local authorities. By addressing these challenges, we will be able to truly engage citizens as collaborators in co-designing their city

Qualitative market research and product development: representations of food and marketing challenges

A new method for analysing social representations from sentences in natural language is presented. The basic nuclei of the social representation of "eating" are extracted from two corpuses, one coming from a large set of definitions from a dictionary, the other from free associations of 2000 French adult subjects. The method shows that "eating", as a mental model, is the connection of "libido", "intake", "foodstuffs", "meal", "filling up" and "living". Further analysis on free associations on "eating well" yields some pragmatic scripts, showing how consumers assemble the basic nuclei into action rules. Results uncover an archaeology of social knowledge, showing some psychological and cultural bases on which lie the contemporary representations of eating. As important marketing issues in the food business today are concerned with the psychological determinants of food behaviour, our method may bring some new tools for market research, and open new data fields to systematic investigation. A paper from an international symposium 'Enjeux actuels du marketing dans l'alimentation et la restauration' held in Montreal, Canada, May 24th to 27th, 1994

Using Social Media as a Source for Understanding Public Perceptions of Archaeology: Research Challenges and Methodological Pitfalls

Digital social science research has had an important impact on the types of methodological approaches to the internet and digital social phenomena, practices and communities. Whilst this paper does not seek to include empirical data, it aims to elaborate further on these debates in digital social research, that is, research on ‘life in digital society’ (Lindgren 2017: 230), using insights from my own research methods. This paper will firstly consider some methodological pitfalls that could sabotage our digital social archaeology research. It will then discuss the importance of understanding the framework and sources of our data. It will outline the two main methodological approaches I have used in my own empirical research to date – ‘thick’ social media data collection and analysis, and digital ethnography. It will discuss some of the many ethical considerations that must be assessed and implemented when undertaking this type of work. I will argue for a methodological pragmatism when undertaking social research in the fields of archaeology and heritage, although this pragmatism can be applied to any field of social study in the digital world

Observing and recommending from a social web with biases

The research question this report addresses is: how, and to what extent, those directly involved with the design, development and employment of a specific black box algorithm can be certain that it is not unlawfully discriminating (directly and/or indirectly) against particular persons with protected characteristics (e.g. gender, race and ethnicity)?Comment: Technical Report, University of Southampton, March 201