Description du projet
Regarder de plus près les SSN
La hausse rapide du nombre d’utilisateurs des sites de réseautage social a entrainé les chercheurs à enquêter sur la fiabilité des «réseaux sociaux signés» (signed social networks ou SSN). Les chercheurs étudient des moyens pour transformer un réseau de relations non signé en un réseau de confiance/méfiance signé. Un éventail de réseaux disponibles, comme Epinions, a commencé à étiqueter des liens de manière explicite soit comme ami/ennemi soit de confiance/méfiance. Le projet TEAMS, financé par l’UE, développera des mécanismes pour détecter les communautés de confiance et apprendre leur dynamique évolutive. Il analysera le mécanisme de représentation des SSN à l’aide d’une analyse de concepts formels pour mettre au point un modèle.
Objectif
Users’ experience with real-world social systems (e.g. Epinions and eBay) witnesses the importance of Signed Social Networks (SSNs) that have wide practical and valuable applications in social media such as opinion guidance, personalized recommendation, and topic identification. However, the diversity of massive social interactions complicates the trust and distrust relations among users in SSNs. In particular, the complexity of distrust relations leads to significant challenges in detecting the trusted communities and capturing their evolutionary patterns.
This research aims to pioneer the innovative mechanisms for detecting the trusted communities and learning the evolutionary dynamics. To this end, we will explore the representation mechanism for SSNs by using the Formal Concept Analysis (FCA) and develop a FCA-based representation model. Next, the mechanisms and corresponding algorithms for detecting trusted communities and identifying their dynamic evolutions will be investigated. This research will provide both theoretical fundamentals and practical techniques for detection and dynamic evolution of trusted communities in SSNs. Moreover, this project can stimulate new research directions and the collaborative opportunities across multiple disciplines, such as social computing, soft computing and networking.
To broaden the fellow’s knowledge horizon, a series of research, training, and knowledge transfer activities are planned. The new knowledge and skills imparted in these activities will further promote the applicant’s research portfolio and significantly enhance his career prosperity. The research will also lay a solid foundation for the long-term and wide-range collaborations between the fellow and the host university, and eventually lead to more extensive and higher impact of research results, from which both EU and China will benefit.
Champ scientifique
Programme(s)
Régime de financement
MSCA-IF-EF-ST - Standard EFCoordinateur
EX4 4QJ Exeter
Royaume-Uni