Contributions à l'étude des réseaux sociaux : propagation, fouille, collecte de données

Le concept de reseau offre un modele de representation pour une grande variete d'objets et de systemes, aussi bien naturels que sociaux, dans lesquels un ensemble d'entites homogenes ou heterogenes interagissent entre elles. Il est aujourd'hui employe couramment pour designer divers types de structures relationnelles. Pourtant, si chacun a une idee plus ou moins precise de ce qu'est un reseau, nous ignorons encore souvent les implications qu'ont ces structures dans de nombreux phenomenes du monde qui nous entoure. C'est par exemple le cas de processus tels que la diffusion d'une rumeur, la transmission d'une maladie, ou meme l'emergence de sujets d'interet commun a un groupe d'individus, dans lesquels les relations que maintiennent les individus entre eux et leur nature s'averent souvent etre les principaux facteurs determinants l'evolution du phenomene. C'est ainsi que l'etude des reseaux est devenue l'un des domaines emergents du 21e siecle appele la "Science des reseaux". Dans ce memoire, nous abordons trois problemes de la science des reseaux: le probleme de la diffusion dans les reseaux sociaux, ou nous nous sommes interesses plus particulierement a l'impact de la dynamique du reseau sur le processus de diffusion, le probleme de l'analyse des reseaux sociaux, dans lequel nous avons propose une solution pour tirer parti de l'ensemble des informations disponibles en combinant les informations sur la structure du reseau et les attributs des noeuds et le probleme central de la collecte de donnees sociales, ou nous nous sommes interesses au cas particulier de la collecte de donnees en milieux sauvages.

[1]  Laurent Brisson,et al.  How to Semantically Enhance a Data Mining Process? , 2008, ICEIS.

[2]  D. Cvetkovic,et al.  Graph theory and molecular orbitals , 1974 .

[3]  Jiawei Han,et al.  gSpan: graph-based substructure pattern mining , 2002, 2002 IEEE International Conference on Data Mining, 2002. Proceedings..

[4]  A. John MINING GRAPH DATA , 2022 .

[5]  Maria A. Kazandjieva,et al.  A high-resolution human contact network for infectious disease transmission , 2010, Proceedings of the National Academy of Sciences.

[6]  Martine Collard,et al.  GT-FLMin: Un Outil Graphique pour l'Extraction de Liens Fréquents dans les Réseaux Sociaux , 2012, EGC.

[7]  Martine Collard,et al.  Sociability vs Network Dynamics: Impact of Two Aspects of Human Behavior on Diffusion Phenomena , 2012, 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining.

[8]  Bénédicte Le Grand,et al.  Conceptual and statistical footprints for social networks' characterization , 2009, SNA-KDD '09.

[9]  Aravaipa Canyon Basin,et al.  Volume 3 , 2012, Journal of Diabetes Investigation.

[10]  Chunju Tseng,et al.  Incorporating Geographical Contacts into Social Network Analysis for Contact Tracing in Epidemiology: A Study on Taiwan SARS Data , 2007, BioSurveillance.

[11]  Éric Daudé,et al.  Exploration de l'effet des types de mobilités sur la diffusion des épidemies , 2005 .

[12]  Sergei O. Kuznetsov,et al.  Concept Stability for Constructing Taxonomies of Web-site Users , 2009, ArXiv.

[13]  Martine Collard,et al.  Detecting movement patterns with wireless sensor networks: application to bird behavior , 2010, MoMM.

[14]  N. Christakis,et al.  The Spread of Obesity in a Large Social Network Over 32 Years , 2007, The New England journal of medicine.

[15]  Martine Collard,et al.  Towards Merging Models of Information Spreading and Dynamic Phenomena in Social Networks , 2011, WSKS.

[16]  Charu C. Aggarwal,et al.  Managing and Mining Graph Data , 2010, Managing and Mining Graph Data.

[17]  Václav Snásel,et al.  Analyzing Social Networks Using FCA: Complexity Aspects , 2009, 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology.

[18]  Philippe Collard,et al.  Mobility and Information Flow: Percolation in a Multi-Agent Model , 2012, ANT/MobiWIS.

[19]  Hugo Miranda,et al.  Middleware for Network Eccentric and Mobile Applications , 2009 .

[20]  Mathias Géry,et al.  Combining Relations and Text in Scientific Network Clustering , 2012, 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining.

[21]  Nitin H. Vaidya,et al.  Proceedings of the 9th annual international conference on Mobile computing and networking , 2003, MobiCom 2003.

[22]  Shilpa Chakravartula,et al.  Complex Networks: Structure and Dynamics , 2014 .

[23]  D. Grémillet,et al.  GPS tracking a marine predator: the effects of precision, resolution and sampling rate on foraging tracks of African Penguins , 2004 .

[24]  Gianni Pavan,et al.  Individual recognition of male Tawny owls (Strix aluco) using spectrograms of their territorial calls , 1991 .

[25]  A. Klovdahl,et al.  Social networks and the spread of infectious diseases: the AIDS example. , 1985, Social science & medicine.

[26]  Peter Knees,et al.  The CoMIRVA Toolkit for Visualizing Music-Related Data , 2007, EuroVis.

[27]  Martine Collard,et al.  How to extract frequent links with frequent itemsets in social networks? , 2012, 2012 Sixth International Conference on Research Challenges in Information Science (RCIS).

[28]  Giorgio Parisi,et al.  Physica A: Statistical Mechanics and its Applications: Editorial note , 2005 .

[29]  Martine Collard,et al.  Frequent Links: An Approach That Combines Attributes and Structure for Extracting Frequent Patterns in Social Networks , 2012, ADBIS.

[30]  Jari Saramäki,et al.  A comparative study of social network models: Network evolution models and nodal attribute models , 2008, Soc. Networks.

[31]  Stefan Bornholdt,et al.  Emergence of a small world from local interactions: modeling acquaintance networks. , 2002, Physical review letters.

[32]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[33]  Bénédicte Le Grand,et al.  Conceptual and Spatial Footprints for Complex Systems Analysis: Application to the Semantic Web , 2009, DEXA.

[34]  M. L. Kent,et al.  Volume 73 , 2005, Environmental Biology of Fishes.

[35]  Nick Cercone,et al.  2001 IEEE International Conference on Data Mining , 2001 .

[36]  Alex Pentland,et al.  Social Sensors for Automatic Data Collection , 2008, AMCIS.

[37]  VoLUME Xxxix,et al.  THE AMERICAN JOURNAL OF SOCIOLOGY , 2010 .

[38]  Eytan Modiano,et al.  Proceedings of the 8th ACM international symposium on Mobile ad hoc networking and computing , 2007, MobiCom 2007.

[39]  Craig E. Wills,et al.  Proceedings of the 13th international conference on World Wide Web , 2004 .

[40]  D. Phan,et al.  From Agent-based Computational Economics Towards Cognitive Economics , 2004 .

[41]  Theo Geisel,et al.  Recurrent host mobility in spatial epidemics: beyond reaction-diffusion , 2011, 1106.3461.

[42]  Joao Antonio Pereira,et al.  Linked: The new science of networks , 2002 .

[43]  M. McPherson,et al.  Birds of a Feather: Homophily in Social Networks , 2001 .

[44]  Martine Collard,et al.  D2SNet: Dynamics of diffusion and dynamic human behaviour in social networks , 2013, Comput. Hum. Behav..

[45]  Hong Cheng,et al.  Graph Clustering Based on Structural/Attribute Similarities , 2009, Proc. VLDB Endow..

[46]  R. Christley,et al.  Infection in social networks: using network analysis to identify high-risk individuals. , 2005, American journal of epidemiology.

[47]  Martine Collard,et al.  How to measure interestingness in data mining: a multiple criteria decision analysis approach , 2007, RCIS.

[48]  Matteo Marsili,et al.  The rise and fall of a networked society: a formal model. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[49]  Martine Collard,et al.  MAX-FLMin: An Approach for Mining Maximal Frequent Links and Generating Semantical Structures from Social Networks , 2012, DEXA.

[50]  Martine Collard,et al.  Social-Based Conceptual Links: Conceptual Analysis Applied to Social Networks , 2012, 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining.

[51]  Alex Lascarides,et al.  Computational Intelligence for Knowledge-Based Systems Design , 2010 .

[52]  Pietro Manzoni,et al.  ANEJOS: a Java based simulator for ad hoc networks , 2001, Future Gener. Comput. Syst..

[53]  Cecilia Mascolo,et al.  Proceedings of the 1st ACM SIGMOBILE workshop on Mobility models , 2008 .

[54]  R. Lathe Phd by thesis , 1988, Nature.

[55]  Alejandro P. Buchmann,et al.  Proceedings of the 22th International Conference on Very Large Data Bases , 1996 .

[56]  Marion B. H. Whyte Family and Social Network , 1958, Mental Health.

[57]  Mark Newman,et al.  Networks: An Introduction , 2010 .

[58]  Martine Collard,et al.  FLMin: An Approach for Mining Frequent Links in Social Networks , 2012, NDT.

[59]  ScienceDirect Computational statistics & data analysis , 1983 .

[60]  Lakhdar Benkobi,et al.  Evaluating elk habitat interactions with GPS collars , 2001 .

[61]  Laks V. S. Lakshmanan,et al.  Proceedings of the 2008 ACM SIGMOD international conference on Management of data , 2008, SIGMOD 2008.

[62]  Lise Getoor,et al.  Link mining: a survey , 2005, SKDD.

[63]  Hongjun Lu,et al.  ReCoM: reinforcement clustering of multi-type interrelated data objects , 2003, SIGIR.

[64]  Dock Bumpers,et al.  Volume 2 , 2005, Proceedings of the Ninth International Conference on Computer Supported Cooperative Work in Design, 2005..

[65]  Martine Collard,et al.  Network-Based Modeling in Epidemiology: An Emphasis on Dynamics , 2012, Int. J. Inf. Syst. Model. Des..

[66]  Jean-Loup Guillaume,et al.  File diffusion in a dynamic peer-to-peer network , 2012, WWW.

[67]  Georges Linarès,et al.  GMM-based acoustic modeling for embedded speech recognition , 2006, INTERSPEECH.

[68]  Madhav V. Marathe,et al.  EpiSimdemics: An efficient algorithm for simulating the spread of infectious disease over large realistic social networks , 2008, 2008 SC - International Conference for High Performance Computing, Networking, Storage and Analysis.

[69]  D. Watts The “New” Science of Networks , 2004 .

[70]  Ivan Stojmenovic,et al.  Handbook of Sensor Networks: Algorithms and Architectures , 2005, Handbook of Sensor Networks.

[71]  Martine Collard,et al.  Diffusion in Dynamic Social Networks: Application in Epidemiology , 2011, DEXA.

[72]  Tony Sheldon,et al.  BMJ: British Medical Journal , 2007 .

[73]  R Wallace,et al.  Social disintegration and the spread of AIDS: thresholds for propagation along 'sociogeographic' networks. , 1991, Social science & medicine.

[74]  M. Newman,et al.  Network theory and SARS: predicting outbreak diversity , 2004, Journal of Theoretical Biology.

[75]  Andrew Hudson-Smith,et al.  Agent Street: An Environment for Exploring Agent-Based Models in Second Life , 2009, J. Artif. Soc. Soc. Simul..

[76]  A. Noymer,et al.  The transmission and persistence of ‘urban legends’: Sociological application of age‐structured epidemic models , 2001, The Journal of mathematical sociology.