Interaction data are identifiable even across long periods of time

Fine-grained records of people’s interactions, both offline and online, are collected at large scale. These data contain sensitive information about whom we meet, talk to, and when. We demonstrate here how people’s interaction behavior is stable over long periods of time and can be used to identify individuals in anonymous datasets. Our attack learns the profile of an individual using geometric deep learning and triplet loss optimization. In a mobile phone metadata dataset of more than 40k people, it correctly identifies 52% of individuals based on their 2-hop interaction graph. We further show that the profiles learned by our method are stable over time and that 24% of people are still identifiable after 20 weeks. Our results suggest that people with well-balanced interaction graphs are more identifiable. Applying our attack to Bluetooth close-proximity networks, we show that even 1-hop interaction graphs are enough to identify people more than 26% of the time. Our results provide strong evidence that disconnected and even re-pseudonymized interaction data can be linked together making them personal data under the European Union’s General Data Protection Regulation

Seeking Magis: a Virtuous Approach to Medical Practice

John Rawls, in his book Justice as Fairness, spends a great deal of time setting up a system of basic liberties to ensure justice within our society. In my thesis, I suggest that rules and objectivity alone are not enough to ensure the moral integrity of society as a whole or the social practices that comprise it. Instead, we ought to first focus on the development of subjective individual character traits so that we can actually understand the function and authority of rules. As an example of how character development ought to proceed, I turn to the practice of modem medicine, which has a very unique perspective on the function of rules and objective perspectives. The objective perspective at work in medicine is known as Disease Theory, which essentially objectively classifies individuals based on their bodily affliction. I argue that this theory and the objectivity inherent to it do not properly treat the suffering of individual persons. Therefore, I turn to Alasdair MacIntyre and his conception of Virtue Theory in order to formulate a proper conduct for individuals within a social practice. This leads to the formulation of five necessary virtues that must be possessed by the modem physician in order to treat patient suffering

Cognitive polyphasia in the MMR controversy: a theoretical and empirical investigation

This thesis examines the hypothesis of cognitive polyphasia proposed by Serge Moscovici in La Psychanalyse, son Image et son Public (1961/1976). Despite its intuitive appeal, the hypothesis remains largely unexplored. This research is an attempt at understanding better the operations of cognitive polyphasia, in particular, at the level of social individuals who have to make sense of the world around them. The hypothesis of cognitive polyphasia is empirically examined through the controversy that surrounded the MMR vaccination programme in the UK between 1998 and 2005. The review of literature proposes a typology of cognitive polyphasia through an examination of empirical studies done by social representations theorists. A theoretical framework for the operationalisation of cognitive polyphasia is then proposed. This includes some elements of social cognition. The methodology chapter presents and discusses the specific methods used in this work, that is, expert interviews with health professionals and media representatives, media analysis of newspaper articles, focus groups and individual interviews with mothers of children of vaccination age. The analysis and findings of this empirical work are then presented in the results chapters focusing on their implications for our understanding of cognitive polyphasia at both the collective and the individual levels. A key finding of this study is the identification of a number of exemplars characteristic of different ways of sense making and of different ways of engaging into cognitive polyphasia. In particular, the study distinguishes between non- and polyphasic groups, that is, between people who have relied exclusively on scientific or narrative types of knowledge versus those who used a combination of types of knowledge to make sense of the MMR controversy. The theoretical implications of this work and the practical lessons that can be drawn from the public�s reactions when faced with scientific controversies are discussed in the conclusion chapter

Optimal Control of Epidemics in the Presence of Heterogeneity

We seek to identify and address how different types of heterogeneity affect the optimal control of epidemic processes in social, biological, and computer networks. Epidemic processes encompass a variety of models of propagation that are based on contact between agents. Assumptions of homogeneity of communication rates, resources, and epidemics themselves in prior literature gloss over the heterogeneities inherent to such networks and lead to the design of sub-optimal control policies. However, the added complexity that comes with a more nuanced view of such networks complicates the generalizing of most prior work and necessitates the use of new analytical methods. We first create a taxonomy of heterogeneity in the spread of epidemics. We then model the evolution of heterogeneous epidemics in the realms of biology and sociology, as well as those arising from practice in the fields of communication networks (e.g., DTN message routing) and security (e.g., malware spread and patching). In each case, we obtain computational frameworks using Pontryagin’s Maximum Principle that will lead to the derivation of dynamic controls that optimize general, context-specific objectives. We then prove structures for each of these vectors of optimal controls that can simplify the derivation, storage, and implementation of optimal policies. Finally, using simulations and real-world traces, we examine the benefits achieved by including heterogeneity in the control decision, as well as the sensitivity of the models and the controls to model parameters in each case