In contrast with centralized recommender systems, social recommendation algorithm is applied to the item rating data on social networks. Meaningful recommendation can be uncovered by the topology of social network as well as the similarity between users. More importantly, this information becomes propagated into the users in the estimated same groups. As the goal of this paper, we propose a nov...

The availability of advanced social interaction sensing technologies provides fine grained data for social network analysis. Although traditional methods of gathering social network data may be subject to human ability to recall social details, people’s rating of their closeness to persons in their network is important. This study assesses the relationship amidst closeness ratings, sensed inter...

Nonnegative Matrix Factorization (NMF) aims to factorize a matrix into two optimized nonnegative matrices and has been widely used for unsupervised learning tasks such as product recommendation based on a rating matrix. However, although networks between nodes with the same nature exist, standard NMF overlooks them, e.g., the social network between users. This problem leads to comparatively low...

Background: Social networks have been widely utilized by a variety of popular review websites, and different users have a different impact on how information propagates through the network. Identifying influential users in such system could be beneficial for advertising purposes. Aim: To estimate the influence propagation probability for social ties in the network using review data which contai...

The advent of online social networks created new prediction opportunities for recommender systems: instead of relying on past rating history through the use of collaborative filtering (CF), they can leverage the social relations among users as a predictor of user tastes similarity. Alas, little effort has been put into understanding when and why (e.g., for which users and what items) the social...

INTRODUCTION Social network analysis has emerged as a promising tool in modern social psychology. This method can be used to examine friend-based social relationships in terms of network theory, with nodes representing individual students and ties representing relationships between students (e.g., friendships and kinships). Using social network analysis, we investigated whether greater severity...

Researchers have been studying hybrid recommender systems which combine user-item rating data with external information in recent years. Some studies suggest that by leveraging additional user and / or item relations, e.g., social network, the performance of the recommendation models can be improved. These studies, nevertheless, mostly utilize a single type of external relationship. Considering...

The authors report on data indicating that having a strong sense of meaning in life makes people more appealing social interactants. In Study 1, participants were videotaped while conversing with a friend, and the interactions were subsequently rated by independent evaluators. Participants who had reported a strong sense of meaning in life were rated as desirable friends. In Study 2, participan...

This paper explores delegation decisions predicated on models of trust and autonomy among agents. In socially rich environments, trust and autonomy of artificial agents are key attributes for rational delegation decisions. Social agents are affected by many social attributes such as benevolence, social exchanges, power, and norms. We present cognitively inspired working models of trust and auto...