Affiliation:
1. King’s College London, London, UK
Abstract
The aim of this article is to provide an understanding of social networks as a useful addition to the standard toolbox of techniques used by system designers. To this end, we give examples of how data about social links have been collected and used in different application contexts. We develop a broad taxonomy-based overview of common properties of social networks, review how they might be used in different applications, and point out potential pitfalls where appropriate. We propose a framework, distinguishing between two main types of social network-based user selection—
personalised
user selection, which identifies target users who may be relevant for a given source node, using the social network around the source as a context, and
generic
user selection or group delimitation, which filters for a set of users who satisfy a set of application requirements based on their social properties. Using this framework, we survey applications of social networks in three typical kinds of application scenarios: recommender systems, content-sharing systems (e.g., P2P or video streaming), and systems that defend against users who abuse the system (e.g., spam or sybil attacks). In each case, we discuss potential directions for future research that involve using social network properties.
Funder
UK Economic and Social Research Council
UK Engineering and Physical Sciences Research Council
Publisher
Association for Computing Machinery (ACM)
Subject
General Computer Science,Theoretical Computer Science
Cited by
7 articles.
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