L’Ecole doctorale : Sciences et Technologies de l’Information et de la Communication
\net le Laboratoire de recherche SAMOVAR<\/p>\n
pr\u00e9sentent l\u2019AVIS DE SOUTENANCE de Madame Monika RAKOCZY<\/p>\n
Autoris\u00e9e \u00e0 pr\u00e9senter ses travaux en vue de l\u2019obtention du Doctorat de l’Universit\u00e9 Paris-Saclay, pr\u00e9par\u00e9 \u00e0 T\u00e9l\u00e9com SudParis en Informatique
\n\u00ab Exploration des interactions humaines pour la mod\u00e9lisation de l’influence dans les r\u00e9seaux sociaux \u00bb<\/p>\n
le VENDREDI 7 JUIN 2019 \u00e0 10h30<\/strong><\/p>\n Salle A003<\/strong><\/p>\n T\u00e9l\u00e9com SudParis – 9 Rue Charles Fourier 91011 Evry<\/strong><\/p>\n Membres du jury :<\/strong><\/p>\n R\u00e9sum\u00e9 :<\/strong><\/p>\n De nos jours, la popularit\u00e9 des r\u00e9seaux sociaux (RS) est en constante progression. En effet, de plus en plus d\u2019utilisateurs interagissent dans le monde virtuel, soit en y exprimant des opinions, en partageant des exp\u00e9riences, en r\u00e9agissant aux avis d\u2019autrui ou encore en \u00e9changeant des id\u00e9es, en fonction de leurs qualit\u00e9s : influents, populaires, dignes de confiance, etc.. Dans la litt\u00e9rature, l\u2019influence a fait l’objet d’une attention particuli\u00e8re ces derni\u00e8res ann\u00e9es. En effet, de nombreux domaines, dont l\u2019Analyse des R\u00e9seaux Sociaux (ARS) et les syst\u00e8mes de recommandation ont \u00e9tudi\u00e9 l\u2019influence, sa d\u00e9tection, la propagation de son effet et sa mesure. Ainsi, des mod\u00e8les d’identification et d’estimation de l’influence sont aujourd’hui largement utilis\u00e9s dans de nombreuses applications d\u00e9di\u00e9es au marketing, aux campagnes politiques\/sociales, etc. De plus, les interactions entre utilisateurs indiquent non seulement l\u2019influence mais aussi la confiance, la popularit\u00e9 ou la r\u00e9putation. Cependant, ces notions sont encore vaguement d\u00e9finies et il n’existe pas de consensus dans la communaut\u00e9 ARS. D\u00e9finir, distinguer et mesurer la force de ces relations entre les utilisateurs posent \u00e9galement de nombreux d\u00e9fis, \u00e0 la fois th\u00e9oriques et pratiques, qui restent \u00e0 explorer. La mod\u00e9lisation de l\u2019influence pose de multiples d\u00e9fis et les m\u00e9thodes actuelles de d\u00e9couverte et d\u2019\u00e9valuation n\u2019explorent pas encore pleinement les diff\u00e9rents types d\u2019interactions et ne sont en g\u00e9n\u00e9ral pas applicables \u00e0 plusieurs RS. En outre, la prise en compte de la dimension temporelle dans le mod\u00e8le d\u2019influence est importante, difficile et n\u00e9cessite un examen plus approfondi. Enfin, l\u2019exploration de liens possibles entre des notions, telles que l\u2019influence et la r\u00e9putation, reste un sujet ouvert. Dans cette th\u00e8se, nous nous focalisons sur les quatre concepts qualifiant les utilisateurs : influence, r\u00e9putation, confiance et popularit\u00e9, pour la mod\u00e9lisation de l’influence. Nous analysons les travaux existants utilisant ces notions et comparons leurs diff\u00e9rentes interpr\u00e9tations. Par cette analyse, nous mettons en avant les caract\u00e9ristiques essentielles que ces concepts devraient inclure, et nous en effectuons une analyse comparative. Cela nous permet d’\u00e9tablir une classification globale des diff\u00e9rentes interpr\u00e9tations des notions selon leur niveau d’abstraction et leurs divergences ; cela constitue la premi\u00e8re, contribution de cette th\u00e8se. En cons\u00e9quence, nous proposons un mod\u00e8le th\u00e9orique de l’influence ainsi qu’une ontologie associ\u00e9e d\u00e9crivant ce concept. Nous pr\u00e9sentons \u00e9galement une variante de l’influence, inexplor\u00e9e \u00e0 ce jour dans le domaine de l\u2019ARS, la micro-influence. Celle-ci cible un ph\u00e9nom\u00e8ne nouveau dans les RS que sont les utilisateurs avec une faible audience, mais fortement impliqu\u00e9s ; ces derniers apparaissent en effet comme ayant un impact fort malgr\u00e9 tout. En s’appuyant sur ces d\u00e9finitions, nous proposons ensuite un mod\u00e8le pratique d\u00e9nomm\u00e9 ARIM (Action-Reaction Influence Model). Ce mod\u00e8le consid\u00e8re le type, la qualit\u00e9, la quantit\u00e9 et la fr\u00e9quence des actions r\u00e9alis\u00e9es par les utilisateurs, et ce en \u00e9tant compatible avec diff\u00e9rents RS. Nous abordons \u00e9galement la quantification de l’influence au cours du temps et la repr\u00e9sentation de ses effets de causalit\u00e9. Pour cela, nous consid\u00e9rons un type sp\u00e9cifique de RS: les r\u00e9seaux de citations, particuli\u00e8rement sensibles au temps. Ainsi, nous proposons un mod\u00e8le, TiDIE (Time Dependent Influence Estimation), qui d\u00e9termine l’influence, sur une p\u00e9riode de temps, entre les communaut\u00e9s de ces r\u00e9seaux. Enfin, nous combinons l\u2019influence et la r\u00e9putation avec le mod\u00e8le TiDIE, afin d\u2019\u00e9tudier les d\u00e9pendances entre elles. Nous proposons une m\u00e9thode de transition, ReTiDIE, utilisant l\u2019influence pour obtenir la r\u00e9putation. Pour chacune de nos approches, des exp\u00e9rimentations ont \u00e9t\u00e9 men\u00e9es sur des jeux de donn\u00e9es r\u00e9els et ont montr\u00e9 la pertinence de nos m\u00e9thodes.<\/p>\n Abstract :<\/strong><\/p>\n Online social networks are constantly growing in popularity. They enable users to interact with one another and shifting their relations to the virtual world. Users utilize social media platforms as a mean for a rich variety of activities. Indeed, users are able to express their opinions, share experiences, react to other users’ views and exchange ideas. Such online human interactions take place within a dynamic hierarchy where we can observe and distinguish many qualities related to relations between users, concerning influential, trusted or popular individuals. In particular, influence within Social Networks (SN) has been a recent focus in the literature. Many domains, such as recommender systems or Social Network Analysis (SNA), measure and exploit users\u2019 influence. Therefore, models discovering and estimating influence are important for current research and are useful in various disciplines, such as marketing, political and social campaigns, recommendations and others. Interestingly, interactions between users can not only indicate influence but also involve trust, popularity or reputation of users. However, all these notions are still vaguely defined and not meeting the consensus in the SNA community. Defining, distinguishing and measuring the strength of those relations between the users are also posing numerous challenges, on theoretical and practical ground, and are yet to be explored. Modelization of influence poses multiple challenges. In particular, current state-of-the-art methods of influence discovery and evaluation still do not fully explore users\u2019 actions of various types, and are not adaptive enough for using different SN. Furthermore, adopting the time aspect into influence model is important, challenging and in need of further examination part of the research. Finally, exploring possible connections and links between coinciding notions, like influence and reputation, remains to be performed. In this thesis, we focus on the qualities of users connected to four important concepts: influence, reputation, trust, and popularity, in the scope of SNA for influence modeling. We analyze existing works utilizing these notions and we compare and contrast their interpretations. Consequently, we emphasize the most important features that these concepts should include and we make a comparative analysis of them. Accordingly, we present a global classification of the notions concerning their abstract level and distinction of the terms from one another, which is a first and required contribution of the thesis. Consequently, we then propose a theoretical model of influence and present influence-related ontology. We also present a distinction of notion not yet explored in SNA discipline — micro-influence, which targets new phenomena of users with a small but highly involved audience, who are observed to be still highly impactful. Basing on the definitions of the concepts, we propose a practical model, called Action-Reaction Influence Model (ARIM). This model considers type, quality, quantity, and frequency of actions performed by users in SN, and is adaptive to different SN types. We also focus on the quantification of influence over time and representation of influence causal effect. In order to do that, we focus on a particular SN with a specific characteristic – citation network. Indeed, citation networks are particularly time sensitive. Accordingly, we propose Time Dependent Influence Estimation (TiDIE), a model for determining influence during a particular time period between communities within time-dependent citation networks. Finally, we also combine two of the abovementioned notions, influence and reputation, in order to investigate the dependencies between them. In particular, we propose a transition method, ReTiDIE, that uses influence for predicting the reputation. For each of the proposed approaches, experiments have been conducted on real-world datasets and demonstrate the suitability of the methods.<\/p>\n","protected":false},"excerpt":{"rendered":" L’Ecole doctorale : Sciences et Technologies de l’Information et de la Communication et le Laboratoire de recherche SAMOVAR pr\u00e9sentent l\u2019AVIS DE SOUTENANCE de Madame Monika RAKOCZY Autoris\u00e9e \u00e0 pr\u00e9senter ses travaux en vue de l\u2019obtention du Doctorat de l’Universit\u00e9 Paris-Saclay, pr\u00e9par\u00e9 \u00e0 T\u00e9l\u00e9com SudParis en Informatique \u00ab Exploration des interactions humaines pour la mod\u00e9lisation de 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\n Mme Amel BOUZEGHOUB,
\nProfesseure, T\u00e9l\u00e9com SudParis, FRANCE <\/td>\n Directrice de th\u00e8se<\/td>\n<\/tr>\n \n Mme Katarzyna WEGRZYN-WOLSKA,
\nProfesseure, EFREI Paris, FRANCE<\/td>\n Examinatrice<\/td>\n<\/tr>\n \n Mme Alda GANCARSKI LOPES,
\nAssociate Professor, T\u00e9l\u00e9com SudParis, FRANCE <\/td>\nExaminatrice<\/td>\n<\/tr>\n \n Mme Lynda TAMINE LECHANI,
\nProfesseure, Paul Sabatier University, FRANCE<\/td>\n Rapporteur<\/td>\n<\/tr>\n \n M. Przemyslaw KAZIENKO,
\nProfesseur, Wroclaw University of Technology, POLOGNE<\/td>\nRapporteur<\/td>\n<\/tr>\n \n M. Cedric DU MOUZA,
\nMa\u00eetre de Conf\u00e9rences, Conservatoire National des Art et M\u00e9tiers, FRANCE<\/td>\n Examinateur<\/td>\n<\/tr>\n \n M. Bogdan CAUTIS,
\nProfesseur, Universit\u00e9 Paris-Sud, FRANCE <\/td>\nExaminateur<\/td>\n<\/tr>\n \n Mme Salima BENBERNOU,
\nProfesseure, Universit\u00e9 Paris-Descarte, FRANCE<\/td>\nExaminatrice<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n