THE ASSOCIATION OF SOCIAL ANHEDONIA WITH ROMANTIC RELATIONSHIP PROCESSES

Social anhedonia is a deficiency in the capacity to experience pleasure from social interactions. This study examined the implications of social anhedonia for romantic relationship functioning, including the association of social anhedonia with sentiments towards romantic partners that are central to relationship functioning (satisfaction, commitment, regard, and care), analogous perceptions of the partner’s sentiments, hostile behavior during relationship conflict, and perception of the partner’s hostile behavior. Data were collected from 281 participants who were involved in romantic relationships. Support was found for social anhedonia’s hypothesized negative association with satisfaction, regard, and care, as well as all four perceived partner sentiments. These associations were independent of attachment anxiety and avoidance. Additionally, attachment avoidance mediated social anhedonia’s relationship with commitment. However, no support was found for social anhedonia’s hypothesized positive association with actual and perceived partner hostile behavior. Results suggest that social anhedonia may undermine the functioning of interpersonal relationships.

ADVERTISEMENT ALLOCATION AND TRUST MECHANISMS DESIGN IN SOCIAL NETWORKS

Social network sites (SNS), such as Facebook, Google+ and Twitter, have attracted hundreds of millions of users daily since their appearance. Within SNS, users connect to each other, express their identity, disseminate information and form cooperation by interacting with their connected peers. The increasing popularity and ubiquity of SNS usage and the invaluable user behaviors and connections give birth to many applications and business models. We look into several important problems within the social network ecosystem. The first one is the SNS advertisement allocation problem. The other two are related to trust mechanisms design in social network setting, including local trust inference and global trust evaluation. In SNS advertising, we study the problem of advertisement allocation from the ad platform's angle, and discuss its differences with the advertising model in the search engine setting. By leveraging the connection between social networks and hyperbolic geometry, we propose to solve the problem via approximation using hyperbolic embedding and convex optimization. A hyperbolic embedding method, \hcm, is designed for the SNS ad allocation problem, and several components are introduced to realize the optimization formulation. We show the advantages of our new approach in solving the problem compared to the baseline integer programming (IP) formulation. In studying the problem of trust mechanisms in social networks, we consider the existence of distrust (i.e. negative trust) relationships, and differentiate between the concept of local trust and global trust in social network setting. In the problem of local trust inference, we propose a 2-D trust model. Based on the model, we develop a semiring-based trust inference framework. In global trust evaluation, we consider a general setting with conflicting opinions, and propose a consensus-based approach to solve the complex problem in signed trust networks.