Éditeur(s) : HAL CCSD RNTI
Résumé : International audience
Nous avons tous déjà eu l’occasion d’effectuer des recherches d’ordremédical sur Internet. Si certains sites spécialisés se refusent à tout diagnosticen ligne, préférant le renvoi vers des professionnels de santé, d’autres en revancheconduisent souvent à des déclarations alarmistes faisant état de situationshumaines difficiles. Dans ce travail, nous étudions l’ampleur de ce phénomèneet montrons que quel que soit le syndrome recherché, les résultats obtenusconduisent toujours à l’énoncé des mots "cancer" ou "tumeur".
RNTI. Extraction et Gestion des Connaissances (EGC), Jan 2014, Rennes, France
Rennes, France

hal-01514251
https://hal.archives-ouvertes.fr/hal-01514251

Éditeur(s) : HAL CCSD
Résumé : International audience
Numerous diffusion models can be found in the literature. Although these models havebeen widely used to address several problems related to diffusion phenomena at the individuallevel, they do not faithfully represent the microscopic mechanisms that take place in the realtransmission processes. Today, the apparition of new communication media allows model togo further by providing data on many real cases of diffusion. In particular, these newapproaches have shown that several dimensions involved in diffusion phenomena are notpresent in current models. In our works, we focus on two original dimensions to address thediffusion problem: the personality and the neutrality of the spreader. Our aim is to understandthe influence of these two dimensions regarding the diffusion behaviours. Our approach hasbeen used to study diffusion of messages related to several events occurred in January 2015.The results obtained provide a new and interesting lighting on the heterogeneity of thediffusion behaviors in function of personality and neutrality levels. This work provides amethodology which may be useful in marketing strategies, for instance the analysis of thefeatures of individuals who talk about their touristic trips in Caribbean. Such an approach mayalso be useful to understand diffusion and exchange behaviors in the Caribbean basin. Froman economic point of view, such an approach could be used for understanding theexpectations, targeting individuals and proposing tailored offers.
20th Biennial General Meeting of The Caribbean Academy of Sciences
Deshaies, France

hal-01514262
https://hal.archives-ouvertes.fr/hal-01514262

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
In this paper, we present an original and formal framework, the D2SNet model designed to combine both the social network evolution and the diffusion dynamics among individuals. We have conducted experiments on three social networks that show identical characteristics as real social networks. A formal definition of the model is provided and we describe its implementation in a simulation tool. We represent human behaviors and information dissemination strategies by standard and synthetic scheme. In a first step, we study the impact of network growing strategies only and we highlight important parameters such as the evolution speed and mainly the kind of strategies that favour or not the spread. Then we study a more complete evolution strategy that involves link creation and deletion. We provide a deep analysis on the impact of each parameter such as evolution speed, creation and deletion probabilities and dynamic human behaviors on the diffusion amplitude and coverage. Our study gives a novel and useful insight in the diffusion process in a dynamic context.
ISSN: 0747-5632

hal-00786164
https://hal.archives-ouvertes.fr/hal-00786164
DOI : 10.1016/j.chb.2012.06.004

Éditeur(s) : HAL CCSD
Résumé : International audience
In this work, we focus on the issue of diffusion in dynamic networks. We begin by proposing a generic framework that merges two essential aspects of the problem: diffusion and network dynamics. Then, our framework is used for comparing effects of two aspects of the human behavior, sociability and network dynamics. On the one hand the dynamics of the network is related to the movements of individuals in a social space that lead ephemeral social proximity contacts. On the other hand the diffusion phenomenon is studied through the epidemic paradigm. The results obtained by simulations provide original insight about how and why the "social dynamics" of individuals, related to the proximity in a social space and its evolutions, influences diffusion phenomena through a population.
International Conference on Advances in Social Networks Analysis and Mining
Istanbul, Turkey

hal-00786162
https://hal.archives-ouvertes.fr/hal-00786162
DOI : 10.1109/ASONAM.2012.104

Éditeur(s) : HAL CCSD
Résumé : International audience
The increasing development of world trade has promoted the spread of diseases. Recent events, like the H1N1 outbreak and spread, have confirmed this tendency. Everyone could observe that this kind of infectious disease often has the ability to cross countries borders and spread rapidly. Preventing, monitoring and controlling the outbreak of these diseases have appeared to be a public health problem of primary importance for years. However, although numerous works have been conducted in order to understand and study epidemics, this subject remains a topical issue because of the complexity of the phenomena. In this paper, we present new opportunities offered by the field of social networks for understanding the spread of infectious diseases. This work focuses both on techniques already used in epidemiology, and very recent works in social network analysis that open new perspectives. We give an overview of methods currently used to model and study the spread of diseases and future directions that the social network approach allows to glimpse.
2011 Fifth International Conference on Research Challenges in Information Science (RCIS)
Gosier, Guadeloupe

hal-00624364
https://hal.archives-ouvertes.fr/hal-00624364
DOI : 10.1109/RCIS.2011.6006866

Éditeur(s) : HAL CCSD
Résumé : International audience
The extraction of knowledge from social networks is an area that has experienced significant growth in recent years. Indeed, thanks to the improvement of storage and calculation capacities, and the heterogeneity of data that can currently be extracted, much effort has been made to go beyond traditional knowledge, by proposing new kinds of patterns that take into account the context. However, while many works were interested in designing new patterns of knowledge or in optimizing existing approaches, few studies have been focused in merging patterns and on the useful knowledge emerging from such fusions. In this work, we focus on two network clustering approaches, able to extract two distinct kinds of patterns, and we seek to understand both the intersections that can exist between them and the knowledge that emerges from their fusion. The first is the classical nodes clustering approach that consists in searching for communities into a network. The second is the search for frequent conceptual links, a new link clustering approach that aims identifying frequent links between groups of nodes sharing common attributes. We propose a set of original measures that aim to evaluate the amount of shared information between these patterns when they are extracted from a same network. These measures are applied to three datasets and demonstrate the interest in simultaneously considering several sources of knowledge.
Advances in Knowledge Discovery and Management (AKDM)

hal-01514227
https://hal.archives-ouvertes.fr/hal-01514227
DOI : 10.1007/978-3-319-45763-5_13

Éditeur(s) : HAL CCSD
Résumé : International audience
A key issue for any project that aims to study endangered animals is the counting process. In this work, we propose an algorithm for automatic counting of singing birds in their habitat by using wireless sensors fitted with microphone. Sensors are used to record audio samples of bird songs and samples are analyzed to extract fingerprints that permit to recognize bird species. This paper details the counting algorithm that uses graph theory and audio inputs comparison. Finally, we demonstrate our scheme efficiency through experimentations.
International Symposium on a World of Wireless, Mobile and Multimedia Networks
Lucca, Italy

hal-00618563
https://hal.archives-ouvertes.fr/hal-00618563
DOI : 10.1109/WoWMoM.2011.5986215

Éditeur(s) : HAL CCSD Elseiver
Résumé : International audience
Social networks are used on a daily basis by millions of individuals who post millions of messages on several topics. The data recorded by these networks provide useful information in order to predict or detect events in the real world. Some diffused messages are misinformation or false rumours, and so, can be the cause of panic or stress situations. In order to avoid and anticipate these critical situations and understand the diffusion phenomenon in general, it is necessary to study and model the propagation of the information. In this sense, several varieties of models have been proposed and some researchers have attempted to identify parameters involved in the information diffusion. In this paper, we introduce well-known diffusion models that generally simplify drastically the process and we present also a survey of more advanced works whether recent or not studying factors that influence the information diffusion. Finally, we give essential perspectives of research toward a more realistic coverage of information diffusion phenomena.
International Conference on Ambient Systems, Networks and Technologies( ANT)
Madeira, Portugal

hal-01586512
https://hal.archives-ouvertes.fr/hal-01586512
DOI : 10.1016/j.procs.2017.05.404

Éditeur(s) : HAL CCSD
Résumé : International audience
In this work, we propose a novel approach for the discovery of frequent patterns in a social network on the basis of both vertex attributes and link frequency. With an analogy to the traditional task of mining frequent item sets, we show that the issue addressed can be formulated in terms of a conceptual analysis that elicits conceptual links. A social-based conceptual link is a synthetic representation of a set of links between groups of vertexes that share similar internal properties. We propose a first algorithm that optimizes the search into the concept lattice of conceptual links and extracts maximal frequent conceptual links. We study the performances of our solution and give experimental results obtained on a sample example. Finally we show that the set of conceptual links extracted provides a conceptual view of the social network.
IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)
Istanbul, Turkey

hal-00786161
https://hal.archives-ouvertes.fr/hal-00786161
DOI : 10.1109/ASONAM.2012.15

Éditeur(s) : HAL CCSD
Résumé : International audience
The paper proposes a new knowledge discovery method called MAX-FLMin for extracting frequent patterns in social networks. Unlike traditional approaches that mainly focus on the network topological structure, the originality of our solution is its ability to exploit information both on the network structure and the attributes of nodes in order to elicit specific regularities that we call "Frequent Links". This kind of patterns provides relevant knowledge about the groups of nodes most connected within the network. First, we detail the method proposed to extract maximal frequent links from social networks. Second, we show how the extracted patterns are used to generate aggregated networks that represent the initial social network with more semantics. Qualitative and quantitative studies are conducted to evaluate the performances of our algorithm in various configurations.
Database (Weston, Conn.) and Expert Systems Applications
Vienna, Austria

hal-00767052
https://hal.archives-ouvertes.fr/hal-00767052
DOI : 10.1007/978-3-642-32600-4_35

Éditeur(s) : HAL CCSD Springer
Résumé : International audience
The study of information dissemination in social networks is of particular importance in many areas as marketing, politics and security for example. Various strategies are being developed to disseminate information, those aimed at disseminating information widely and those aimed at disseminating information in a more confidential manner to make it scarce. In this paper, we adapt a model dedicated to spreading rumours by word of mouth in a physical space to the context of social networks. We compare two modes of dissemination based on profusion or scarcity and study the impact of the choice of the initial node. The results obtained show to what extent each mode exploits the social network topology and especially the influence of hubs.
International Conference on Complex Networks and Their Applications (COMPLEX NETWORK)
Lyon, France

hal-01637573
https://hal.archives-ouvertes.fr/hal-01637573

Éditeur(s) : HAL CCSD
Résumé : National audience
Traditional network generation models attempt to replicate global structural properties (degree distribution, average distance, clustering coefficient, communities, etc.) through synthetic link formation mechanisms such as triadic closure or preferential attachment. In this work, we study the evolution of a very big communication network coming from mobile telephony and we analyse the link formation process. A first study conducted on the standard mechanisms allows observing that several mechanisms are responsible for the properties observed in this network. In a second study, we characterize more precisely the link formation process by searching for correlations between the probability of creating a new link and some individual properties such as the degree, the clustering coefficient and the age of the nodes.
Conférence sur les modèles et l'analyse des réseaux : Approches mathématiques et informatiques
Saint-Etienne, France

hal-00873990
https://hal.archives-ouvertes.fr/hal-00873990

Éditeur(s) : HAL CCSD
Résumé : International audience
In real world situations, each person is generally in contact with only a small fraction of the entire population and exchange information through these interactions. Their number and their frequency vary from one to another individual and may be much depending on mobility of individuals. The objective of this article is to better understand how human mobility may have an impact on mobile social networking systems. This should help to answer a question as: "How might an information, a rumor, a pathogen, etc., driven by physical proximity, spread through a population?". We present a first stage of our work in which we focus on percolation processes as information flow mechanisms. We propose a synthetic mobility model and we define an artificial world populated by heterogeneous agents who differ in their mobility. Simulations are conducted on a multi-agent programmable environment. Our experimental results clearly demonstrate positive correlations between agent mobility factors and percolation thresholds.
Procedia CS

hal-00767043
https://hal.archives-ouvertes.fr/hal-00767043
DOI : 10.1016/j.procs.2012.06.007

Éditeur(s) : HAL CCSD ACM
Résumé : International audience
This study presents two algorithms that count birds with wireless sensors equipped with microphones. Audio inputs are parametrized to get some kind of fingerprints which are used to recognize the song of the birds in a classification process. Afterward, counting algorithms derive an estimate of the number of singing birds in the habitat. Unlike traditional approaches which leverage the audio waveform to get the location of the targets, we use a trilateration technique on graphs derived from the detection of the birds. These graphs exhibit nice properties which enable the finding of the estimate in polynomial time. Further, experiments are conducted and confirmm the efficiency of our counting algorithms even in the presence of noise.
Proceedings of the 6th ACM symposium on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks
New York, United States

hal-00602263
https://hal.archives-ouvertes.fr/hal-00602263
DOI : 10.1145/1641876.1641891

Éditeur(s) : HAL CCSD
Résumé : International audience
L'émergence des nouveaux moyens de communication tels que les blogs, les journaux en ligne ou les réseaux sociaux nous permettent d'aller plus loin dans la compréhension des comportements humains. En effet, ces espaces d'échange publiques sont aujourd'hui fermement ancrés dans nos sociétés modernes et s'avèrent être de puissants capteurs des comportements sociaux et des mouvements d’opinions. Dans ce travail, nous nous intéressons à la diffusion d'informations et cherchons à comprendre quelles sont les conditions dans lesquelles une personne décide de s'exprimer sur un sujet. Nous proposons pour cela un ensemble de mesures qui visent à caractériser les comportements de diffusion. Nos mesures ont été utilisées sur les messages liés à deux événements ayant eu lieu au mois de Janvier 2015: la présentation par Microsoft d'un nouveau casque de réalité virtuelle et l'élection d'un parti politique de gauche radical en Grèce.
Les écosystèmes numériques et la démocratisation informationnelle : Intelligence collective, Développement durable, Interculturalité, Transfert de connaissances
Schoelcher, France

Droits : info:eu-repo/semantics/OpenAccess
hal-01258322
https://hal.univ-antilles.fr/hal-01258322
https://hal.univ-antilles.fr/hal-01258322/document
https://hal.univ-antilles.fr/hal-01258322/file/Erick%20STATTNER.pdf

Éditeur(s) : HAL CCSD
Résumé : International audience
In the network modeling area, the most widely used definition of a "pattern" is that of a subgraph, a notion that considers only the network topological structure. While this definition has been very useful for extracting subgraphs frequently found in a network or a set of networks, it does not take into account the node attributes, an intrinsic component of social networks that often provides relevant information on the role or the position of a node in a network. In this paper, we propose a novel approach for extracting frequent patterns in social networks, called frequent link mining, based on the search for particular patterns that combine information on both network structure and node attributes. This kind of patterns, that we call frequent links, provides knowledge on the groups of nodes connected in the social network. In this article, we detail the method proposed for extracting frequent links and discuss its flexibility and its complexity. We demonstrate the efficiency of our solution by carrying out qualitative and quantitative studies.
Advances in Database (Weston, Conn.)s and Information Systems
Poznań, Poland

hal-00767050
https://hal.archives-ouvertes.fr/hal-00767050
DOI : 10.1007/978-3-642-33074-2_28

Éditeur(s) : HAL CCSD
Résumé : International audience
Dans ce travail, nous analysons les données concernant les articles publiés à la conférence EGC. Notre objectif est d’identifier et de comprendre les tendances en matière de collaborations. Pour ce faire, nous adoptons une modélisation descriptive, à travers une approche réseau qui consiste à générer tout d’abord le réseau de collaborations des auteurs à partir des données. Nous enrichissons ensuite les noeuds de ce réseau d’une dizaine d’attributs individuels extraits à partir des données. Enfin, nous recherchons des vues conceptuelles, une approche récente de clustering de liens, qui permet de synthétiser des réseaux en mettant en évidence les ensembles d’attributs retrouvés fréquemment liés dans le réseau. Les résultats obtenus montrent les tendances existantes dans les comportements de collaborations. Dans ce papier, nous présentons ces tendances et montrons comment elles évoluent selon différents seuils d’extraction.
Extraction et gestion des connaissances
Reims, France

hal-01312559
https://hal.archives-ouvertes.fr/hal-01312559

Éditeur(s) : HAL CCSD
Résumé : International audience
While the impact of network properties on information spread- ing is now widely studied, in uence of network dynamics is very little known. In this paper, we study how evolution mechanisms tradition- ally observed within social networks can a ect information di usion. We present an approach that merges two models: model of informa- tion di usion through social networks and model of network evolution. Since epidemics provide a reference in application domains of information spreading, we measure the impact of basic network structure changes on epidemic peak value and timing. Then we investigate observed trends in terms of changes appearing in the network structure. Our results provide promising results on how and why network dynamics is a strong param- eter to integrate in requirements for information spreading modelling.
World Summit on the Knowledge Society
Mykonos, Greece

hal-00768405
https://hal.archives-ouvertes.fr/hal-00768405

Éditeur(s) : HAL CCSD Springer
Résumé : International audience
Numerous methods have been proposed in order to perform clustering from social networks. While significant works have been carried out on the design of new approaches, able to search for various kinds of clusters, a major challenge concerns the scalability of these approaches. Indeed, given the mass of data that can now be collected from online social networks, particularly from social platforms, it is important to have efficient methods for exploring and analyzing these very large amount of data. One of the recent social network clustering approaches is the extraction of conceptual links, a new approach that performs link clustering by exploiting both the structure of the network and attributes of nodes to identify strong links between groups of nodes in which nodes share common attributes. In this paper, we focus on the optimization of the search for conceptual links. In particular, we propose PALM, a parallel algorithm that aims to improve the efficiency of the extraction by simultaneously exploring several areas of the search space. For this purpose, we begin by demonstrating that the solution space forms a concept lattice. Then, we propose an approach that explores in parallel the branches of the lattice while reducing the search space based on various properties of conceptual links. We demonstrate the efficiency of the algorithm by comparing the performances with the original extraction approach. The results obtained show a significant gain on the computation time.
28th International Conference on Database and Expert Systems Applications (DEXA)
Lyon, France

hal-01637554
https://hal.archives-ouvertes.fr/hal-01637554
DOI : 10.1007/978-3-319-64471-4_21

Éditeur(s) : HAL CCSD RNTI
Résumé : International audience
De nouvelles approches ont permis de constater que plusieurs dimensions impliquées dansdes cas réels de diffusion ne sont pas prises en compte dans les modèles traditionnels. Dansla littérature, on retrouve la nature du message en termes de polarité (Naveed et al., 2011), lesujet du message (Wu et al., 2011), la structure du réseau local (Cheng et al., 2014), etc. Dansce travail, nous abordons le problème de la diffusion en mettant l’accent sur deux dimensionsoriginales : la personnalité de l’utilisateur et le degré de neutralité de ses messages.
RNTI. Extraction et Gestion des Connaissances (EGC), Jan 2017, Grenoble, France.
Grenoble, France

hal-01514246
https://hal.archives-ouvertes.fr/hal-01514246