Les enquêtes sur le SIDA en Afrique

A travers cet article est analysé l'intérêt des enquêtes sur le SIDA pour mesurer l'ampleur de la maladie au sein de la population, mais également pour analyser les connaissances et attitudes vis-à-vis de cette maladie afin de mieux organiser les campagnes de prévention. Il s'agit donc de mener d'une part des enquêtes de type épidémiologique mais également de type socio-démographique et anthropologique pour étudier les attitudes face à la maladie. (Résumé d'auteur

User-Centred BCI Videogame Design

International audienceThis chapter aims to offer a user-centred methodological framework to guide the design and evaluation of Brain-Computer Interface videogames. This framework is based on the contributions of ergonomics to ensure these games are well suited for their users (i.e., players). It provides methods, criteria and metrics to complete the different phases required by ae human-centred design process. This aims to understand the context of use, specify the user needs and evaluate the solutions in order to define design choices. Several ergonomic methods (e.g., interviews, longitudinal studies, user based testing), objective metrics (e.g., task success, number of errors) and subjective metrics (e.g., mark assigned to an item) are suggested to define and measure the usefulness, usability, acceptability, hedonic qualities, appealingness, emotions related to user experience, immersion and presence to be respected. The benefits and contributions of the user centred framework for the ergonomic design of these Brain-Computer Interface Videogames are discussed

Fast unfolding of communities in large networks: 15 years later

The Louvain method was proposed 15 years ago as a heuristic method for the fast detection of communities in large networks. During this period, it has emerged as one of the most popular methods for community detection, the task of partitioning vertices of a network into dense groups, usually called communities or clusters. Here, after a short introduction to the method, we give an overview of the different generalizations and modifications that have been proposed in the literature, and also survey the quality functions, beyond modularity, for which it has been implemented

Revealing intricate properties of communities in the bipartite structure of online social networks

International audienceMany real-world networks based on human activities exhibit a bipartite structure. Although bipartite graphs seem appropriate to analyse and model their properties, it has been shown that standard metrics fail to reproduce intricate patterns observed in real networks. In particular, the overlapping of the neighbourhood of communities are difficult to capture precisely. In this work, we tackle this issue by analysing the structure of 4 different real-world networks coming from online social activities. We first analyse their structure using standard metrics. Surprisingly, the clustering coefficient turns out to be less relevant than the redundancy coefficient to account for overlapping patterns. We then propose new metrics, namely the dispersion coefficient and the monopoly, and show that they help refining the study of bipartite overlaps. Finally, we compare the results obtained on real networks with the ones obtained on random bipartite models. This shows that the patterns captured by the redundancy and the dispersion coefficients are strongly related to the real nature of the observed overlaps

Une approche à base de proximité pour la détection de communautés egocentrées

International audienceNous proposons ici une approche performante pour déplier la structure communautaire egocentrée sur un sommet d'un gaphe. Nous montrons que, bien que chaque sommet d'un réseau appartienne en général à plusieurs communautés, il est souvent possible d'identifier une communauté unique si l'on considère deux sommets bien choisis. La méthodologie que nous proposons repose sur cette notion de communauté multi-egocentrée ainsi que sur l'utilisation d'une mesure de proximité dérivée de techniques de dynamique d'opinion, la carryover opinion. Cette approche pallie les limites des fonctions de qualité traditionnellement utilisées pour la détection de communautés egocentrées, et consiste à étudier les irrégularités dans la décroissance de cette mesure de proximité

Clustering in P2P exchanges and consequences on performances.

We propose here an analysis of a rich dataset which gives an exhaustive and dynamic view of the exchanges processed in a running eDonkey system. We focus on correlation in term of data exchanged by peers having provided or queried at least one data in common. We introduce a method to capture these correlations (namely the data clustering), and study it in detail. We then use it to propose a very simple and efficient way to group data into clusters and show the impact of this underlying structure on search in typical P2P systems. Finally, we use these results to evaluate the relevance and limitations of a model proposed in a previous publication. We indicate some realistic values for the parameters of this model, and discuss some possible improvements

Multi-ego-centered communities in practice

International audienceWe propose here a framework to unfold the ego-centered community structure of a given node in a network. The framework is not based on the optimization of a quality function, but on the study of the irregularity of the decrease of a proximity measure. It is a practical use of the notion of multi-ego-centered community and we validate the pertinence of the approach on benchmarks and a real-world network of wikipedia pages