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
Summary
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.
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