This paper analyzes a model where investors use a credit rating to decide whether to finance a firm. The rating quality depends on the credit rating agency’s (CRA) effort, which is unobservable. We analyze optimal compensation contracts for the CRA that differ depending on whether the firm, investors or a social planner orders the rating. We find that rating errors are larger when the firm orde...

In an online community of any size, every user garners reputations for different contexts through interactions with other users. When any user in the online community is interested in a certain context, the user would value the opinions of those users of high repute with respect to that context. However, if the online community is of any significant size, a user might not know every other user ...

The rapid growth of information enables a large increase in needs of recommendation. To satisfy this need, Collaborative Filtering and Social Filtering are adopted as solutions for personalized music recommendation. Contemporary recommender systems based on collaborative filtering and social filtering always suffer problems of unreliable item similarity, rating sparsity, lack of rating and un-r...

Social participatory sensing is a newly proposed paradigm that tries to address the limitations of participatory sensing by leveraging online social networks as an infrastructure. A critical issue in the success of this paradigm is to assure the trustworthiness of contributions provided by participants. In this paper, we propose an application-agnostic reputation framework for social participat...

To ensure that social networks (e.g. opinion consensus, cooperative estimation, distributed learning and adaptation etc.) proliferate and efficiently operate, the participating agents need to collaborate with each other by repeatedly sharing information. However, sharing information is often costly for the agents while resulting in no direct immediate benefit for them. Hence, lacking incentives...

Current social recommendations based on Graph Neural Networks (GNNs) often neglect to extract rating bias from user and item statistics, leading misinterpreting real preferences. For example, a high with lenient standards average does not always indicate preference for the item. This situation highlights inherent flaws in existing recommendation algorithms that do adequately account ratings tre...

achieving the millennium development goals has proven to be a real challenge. providing evidence on cost-effective interventions did not prove to be sufficient to secure the trust of national authorities, health care providers and patients. introducing change in a health system requires a good understanding of the relationships between the actors of the system. social network analysis can provi...

Aggregate answer ratings serve as a metric of collective intelligence in social Q&A communities. The patterns by which participants in a social Q&A community rate and recommend answers are analyzed through the lens of first-mover advantage, to address the question of whether the first answer posted has a ratings advantage over those subsequently submitted. As part of a long-term participant obs...

background and objectives: while social network analysis has left a remarkable practical impact in the healthcare field, the potential implication of this methodology in the primary health domain is poorly researched. hence, this study aimed to explore the use and usefulness social network analysis in the context of primary health care. methods: the health volunteers of imam ali health center i...