Descrizione del progetto
Uno sguardo più attento agli SSN
Il rapido aumento del numero di utenti sui siti di socializzazione in rete ha portato i ricercatori ad approfondire l’affidabilità dei «signed social network (SSN)», ovvero recanti informazioni sulla tipologia di collegamento (positivo o negativo) esistente tra gli utenti. I ricercatori stanno studiando modalità per trasformare una rete di conoscenze prive di segno positivo o negativo in una rete di fiducia/sfiducia connotata in tal senso. Diverse reti disponibili come Epinions hanno iniziato a etichettare esplicitamente i collegamenti come amico/nemico o fiducia/sfiducia. Il progetto TEAMS, finanziato dall’UE, svilupperà meccanismi per rilevare le comunità fidate e apprenderne le dinamiche evolutive. Esso esplorerà il meccanismo di rappresentazione per gli SSN utilizzando l’analisi formale dei concetti per sviluppare un modello.
Obiettivo
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.
Campo scientifico
Programma(i)
Argomento(i)
Meccanismo di finanziamento
MSCA-IF-EF-ST - Standard EFCoordinatore
EX4 4QJ Exeter
Regno Unito