In the Internet era, online social media emerged as the main tool for sharing opinions and information among individuals. In this work, we study an adaptive model of a social network where directed links connect users with similar tastes, and over which information propagates through social recommendation. Agent-based simulations of two different artificial settings for modeling user tastes are compared with patterns seen in real data, suggesting that users differing in their scope of interests is a more realistic assumption than users differing only in their particular interests. We further introduce an extensive set of similarity metrics based on users' past assessments, and evaluate their use in the given social recommendation model with both artificial simulations and real data. Superior recommendation performance is observed for similarity metrics that give preference to users with small scope — who thus act as selective filters in social recommendation.

Cimini, G., Zeng, A., Medo, M., Chen, D. (2013). The Role of taste Affinity in Agent-Based Models for Social Recommendation. ADVANCES IN COMPLEX SYSTEM, 16(04n05) [10.1142/S0219525913500094].

The Role of taste Affinity in Agent-Based Models for Social Recommendation

CIMINI G
;
2013-01-01

Abstract

In the Internet era, online social media emerged as the main tool for sharing opinions and information among individuals. In this work, we study an adaptive model of a social network where directed links connect users with similar tastes, and over which information propagates through social recommendation. Agent-based simulations of two different artificial settings for modeling user tastes are compared with patterns seen in real data, suggesting that users differing in their scope of interests is a more realistic assumption than users differing only in their particular interests. We further introduce an extensive set of similarity metrics based on users' past assessments, and evaluate their use in the given social recommendation model with both artificial simulations and real data. Superior recommendation performance is observed for similarity metrics that give preference to users with small scope — who thus act as selective filters in social recommendation.
2013
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore FIS/02 - FISICA TEORICA, MODELLI E METODI MATEMATICI
Settore FIS/03 - FISICA DELLA MATERIA
English
https://www.worldscientific.com/doi/abs/10.1142/S0219525913500094
Cimini, G., Zeng, A., Medo, M., Chen, D. (2013). The Role of taste Affinity in Agent-Based Models for Social Recommendation. ADVANCES IN COMPLEX SYSTEM, 16(04n05) [10.1142/S0219525913500094].
Cimini, G; Zeng, A; Medo, M; Chen, D
Articolo su rivista
File in questo prodotto:
File Dimensione Formato  
1301.4417.pdf

solo utenti autorizzati

Descrizione: Pre-print
Licenza: Non specificato
Dimensione 447.56 kB
Formato Adobe PDF
447.56 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/234144
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 1
social impact