Cimini, Giulio and Zeng, An and Medo, Matúš and Chen, Duanbing The Role of Taste Affinity in Agent-Based Models for Social Recommendation. Advances in Complex Systems, 16 (04n05). p. 1350009. ISSN 0219-5259 (2013)
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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.
| Item Type: | Article |
|---|---|
| Identification Number: | https://doi.org/10.1142/S0219525913500094 |
| Uncontrolled Keywords: | Taste similarity, Agent-based modeling, Adaptive complex networks, Information diffusion and filtering, Social recommendation |
| Subjects: | H Social Sciences > H Social Sciences (General) Q Science > QC Physics |
| Research Area: | Economics and Institutional Change |
| Depositing User: | Caterina Tangheroni |
| Date Deposited: | 06 Nov 2015 12:10 |
| Last Modified: | 06 Nov 2015 12:10 |
| URI: | http://eprints.imtlucca.it/id/eprint/2846 |
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