{"id":1125,"date":"2018-12-11T14:42:32","date_gmt":"2018-12-11T13:42:32","guid":{"rendered":"https:\/\/samovar2022.int-evry.fr\/index.php\/2018\/12\/11\/modele-davis-de-consensus-dans-les-reseaux-sociaux-en-ligne-base-sur-limpact-des-utilisateurs-influents\/"},"modified":"2020-09-04T18:45:45","modified_gmt":"2020-09-04T16:45:45","slug":"modele-davis-de-consensus-dans-les-reseaux-sociaux-en-ligne-base-sur-limpact-des-utilisateurs-influents","status":"publish","type":"post","link":"https:\/\/samovar.telecom-sudparis.eu\/index.php\/2018\/12\/11\/modele-davis-de-consensus-dans-les-reseaux-sociaux-en-ligne-base-sur-limpact-des-utilisateurs-influents\/","title":{"rendered":"\u00ab Mod\u00e8le d’avis de consensus dans les r\u00e9seaux sociaux en ligne bas\u00e9 sur l’impact des utilisateurs influents \u00bb"},"content":{"rendered":"

AVIS DE SOUTENANCE de Monsieur Amir MOHAMMADINEJAD<\/strong><\/p>\n

Autoris\u00e9 \u00e0 pr\u00e9senter ses travaux en vue de l\u2019obtention du Doctorat de T\u00e9l\u00e9com SudParis avec l’Universit\u00e9 Paris 6 en Informatique
\n\u00ab Mod\u00e8le d’avis de consensus dans les r\u00e9seaux sociaux en ligne bas\u00e9 sur l’impact des utilisateurs influents \u00bb<\/p>\n

le 4 d\u00e9cembre 2018 \u00e0 14:00 – Salle A003<\/strong>
\nAdresse : T\u00e9l\u00e9com SudParis – 9 rue Charles Fourier – 91000 Evry<\/p>\n

Membres du jury :<\/strong><\/p>\n\n\n\n\n\n\n\n\n
Directeur de th\u00e8se <\/td>\n No\u00ebl CRESPI – Professeur<\/td>\n<\/tr>\n
Encadrant <\/td>\n Reza FARAHBAKHSH – Chercheur – T\u00e9l\u00e9com SudParis<\/td>\n<\/tr>\n
Rapporteurs <\/td>\nGabriella PASI – Professeure – Universit\u00e9 de Milan Bicocca – Italie<\/td>\n<\/tr>\n
Rapporteurs <\/td>\nAbdelhamid MELLOUK – Professeur – Universit\u00e9 Paris-Est-Cr\u00e9teil<\/td>\n<\/tr>\n
Examinateurs<\/td>\nMai-Trang NGUYEN – Ma\u00eetre de conf\u00e9rences – Universit\u00e9 Paris 6<\/td>\n<\/tr>\n
Examinateurs<\/td>\nIoan Marius BILASCO – Ma\u00eetre de conf\u00e9rences – Universit\u00e9 de Lille 1<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

R\u00e9sum\u00e9 :<\/strong><\/p>\n

Cette th\u00e8se s’int\u00e9resse particuli\u00e8rement aux sites de vente en ligne et \u00e0 leurs r\u00e9seaux sociaux. La propention des utilisteurs utiliser ces sites Web tels qu\u2019Ebay et Amazon est de plus en plus importante en raison de leur fiabilit\u00e9. Les consommateurs se r\u00e9f\u00e8rent \u00e0 ces sites Web pour leurs besoins et en deviennent clients. L’un des d\u00e9fis \u00e0 relever est de fournir les informations utiles pour aider les clients dans leurs achats. Ainsi, une question sous-jacente \u00e0 la th\u00e8se cherche \u00e0 r\u00e9pondre est de savoir comment fournir une information compl\u00e8te aux clients afin de les aider dans leurs achats. C’est important pour les sites d’achats en ligne car cela satisfait les clients par ces informations utiles.<\/p>\n

Pour surmonter ce probl\u00e8me, trois \u00e9tudes sp\u00e9cifiques ont \u00e9t\u00e9 r\u00e9alis\u00e9es : (1) Trouver les utilisateurs influents, (2) Comprendre la propagation d’opinion et (3) Agr\u00e9ger les opinions. Dans la premi\u00e8re partie, la th\u00e8se propose une m\u00e9thodologie pour trouver les utilisateurs influents du r\u00e9seau qui sont essentiels pour une propagation pr\u00e9cise de l’opinion. Pour ce faire, les utilisateurs sont class\u00e9s en fonction de deux scores : optimiste et pessimiste. Dans la deuxi\u00e8me partie, une nouvelle m\u00e9thodologie de propagation de l’opinion est pr\u00e9sent\u00e9e pour parvenir \u00e0 un accord et maintenir la coh\u00e9rence entre les utilisateurs, ce qui rend l’agr\u00e9gation possible. La propagation se fait en tenant compte des impacts des utilisateurs influents et des voisins. Enfin, dans la troisi\u00e8me partie, l’agr\u00e9gation des avis est propos\u00e9e pour rassembler les avis existants et les pr\u00e9senter comme des informations utiles pour les clients concernant chaque produit du site de vente en ligne. Pour ce faire, l’op\u00e9rateur de calcul de la moyenne pond\u00e9r\u00e9e et les techniques floues sont utilis\u00e9es.<\/p>\n

La th\u00e8se pr\u00e9sente un mod\u00e8le d’opinion consensuelle dans les r\u00e9seaux. Les travaux peuvent s’appliquer \u00e0 tout groupe qui a besoin de trouver un avis parmi les avis de ses membres. Par cons\u00e9quent, le mod\u00e8le propos\u00e9 dans la th\u00e8se fournit un taux pr\u00e9cis et appropri\u00e9 pour chaque produit des sites d’achat en ligne.<\/p>\n

Abstract:<\/strong><\/p>\n

Online Social Networks are increasing and piercing our lives such that almost every person in the world has a membership at least in one of them. Among famous social networks, there are online shopping websites such as Amazon, eBay and other ones which have members and the concepts of social networks apply to them. This thesis is particularly interested in the online shopping websites and their networks. According to the statistics, the attention of people to use these websites are growing due to their reliability. The consumers refer to these websites for their need (which could be a product, a place to stay, or home appliances) and become their customers. One of the challenging issues is providing useful information to help thecustomers in their shopping. Thus, an underlying question the thesis seeks to answer is how to provide a comprehensive information to the customers in order to help them in their shopping. This is important for the online shopping websites as it satisfies the customers by this useful information and as a result increases their customers and the benefits of both sides.
\nTo overcome the problem, three specific connected studies are considered: (1) Finding the influential users, (2) Opinion Propagation and (3) Opinion Aggregation. In the first part, the thesis proposes a methodology to find the influential users in the network who are essential for an accurate opinion propagation. To do so, the users are ranked based on two scores namely optimist and pessimist. In the second part, a novel opinion propagation methodology is presented to reach an agreement and maintain the consistency among users which subsequently, makes the aggregation feasible. The propagation is conducted considering the impacts of the influential users and the neighbors. Ultimately, in the third part, the opinion aggregation is proposed to gather the existing opinions and present it as the valuable information to the customers regarding each product of the online shopping website. To this end, the weighted averaging operator and fuzzy techniques are used.
\nThe thesis presents a consensus opinion model in signed and unsigned networks. This solution can be applied to any group who needs to find a plenary opinion among the opinions of its members. Consequently, the proposed model in the thesis provides an accurate and appropriate rate for each product of the online shopping websites that gives a precious information to their customers and helps them to have a better insight regarding the products.<\/p>\n","protected":false},"excerpt":{"rendered":"

AVIS DE SOUTENANCE de Monsieur Amir MOHAMMADINEJAD Autoris\u00e9 \u00e0 pr\u00e9senter ses travaux en vue de l\u2019obtention du Doctorat de T\u00e9l\u00e9com SudParis avec l’Universit\u00e9 Paris 6 en Informatique \u00ab Mod\u00e8le d’avis de consensus dans les r\u00e9seaux sociaux en ligne bas\u00e9 sur l’impact des utilisateurs influents \u00bb le 4 d\u00e9cembre 2018 \u00e0 14:00 – Salle A003 Adresse 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