Abstract

With the advancement of computer and network technologies, Internet-based social networks called social networking services have become popular. Trust is a crucial basis for interactions among parties in social networks. Based on trust scores of direct links between parties, a trust sensitivity analysis can help identify which direct link(s) in a social network contributes the most to a trust relationship between parties who are not directly connected in the network. This paper generalizes the research object from two-state social networks to multistate social networks since the trust grade for people in a real social connection may have multiple levels. We model asymmetric multitrust level and multiparty social network systems and propose a probabilistic method based on multivalued decision diagrams (MDDs) to perform trust sensitivity analysis of social networks. Numerical examples are provided to demonstrate the application of the proposed methodology.

Highlights

  • A social network is traditionally a conception of social science that uses actors and relations to indicate the social relationships or interactions between actors [1]

  • Our efforts are focused on modeling asymmetric multitrust level and multiparty social network systems and proposing a probabilistic method based on multivalued decision diagrams (MDDs) to perform trust sensitivity and importance analysis of social networks

  • For trust sensitivity analyses of twoparty multistate social networks, we propose an algorithm based on Birnbaum’s measure as follows

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Summary

INTRODUCTION

A social network is traditionally a conception of social science that uses actors (individuals, groups, or organizations) and relations to indicate the social relationships or interactions between actors [1]. Xing and Amari [22] analyzed two-party trust sensitivity in social networks and presented a binary decision diagram (BDD)-based algorithm for trust sensitivity analysis in social networks. Our efforts are focused on modeling asymmetric multitrust level and multiparty social network systems and proposing a probabilistic method based on multivalued decision diagrams (MDDs) to perform trust sensitivity and importance analysis of social networks. The remainder of this paper is organized as follows: Section II describes the basics of MDDs. Section III presents the proposed MDD-based method for sensitivity analysis of a two-party multistate social network. A social network is represented using a probabilistic directed graph G(V , E) It contains a set V of nodes and a set E of direct links between parties with a direct trust relationship.

SENSITIVITY ANALYSIS
CONCLUSION

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