Systems Applications of Social Networks

TL;DR

This paper explores how social network data can be integrated into system design, providing a taxonomy, a framework for user selection, and surveying applications like recommendations, content sharing, and security.

Contribution

It introduces a comprehensive framework for using social networks in system applications, including a taxonomy and application scenarios, highlighting future research directions.

Findings

Social networks can enhance user targeting and content recommendation.

Framework differentiates personalized and generic user selection.

Applications include recommender systems, content sharing, and security measures.

Abstract

The aim of this article is to provide an understanding of social networks as a useful addition to the standard tool-box of techniques used by system designers. To this end, we give examples of how data about social links have been collected and used in di erent application contexts. We develop a broad taxonomy-based overview of common properties of social networks, review how they might be used in di erent 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 identi es 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 lters 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 which 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.