Multi-modal Social Networks (MSNs) allow users to form explicit (by adding new friends in their network) or implicit (by similarly co-rating items) social networks. Previous research work was limited either to the prediction of new relationships among users (i.e. Link Prediction problem) or to the prediction of item ratings (i.e. Rating Prediction problem and Item Recommendations). Recent link ...

We study a rating system in which a set of individuals (e.g., the customers of a restaurant) evaluate a given service (e.g, the restaurant), with their aggregated opinion determining the probability of all individuals to use the service and thus its generated revenue. We explicitly model the influence relation by a social network, with individuals being influenced by the evaluation of their tru...

Study objective: It is increasingly recognised that different dimensions of social inequality may be linked to health by different pathways. Furthermore, factors operating at the individual level such as employment conditions may affect health in a different way from household level factors. The paper examines the associations between self rated health and four measures of social position— occu...

BACKGROUND Traditional focus groups have been essential to facial aesthetics research. Although they are currently the criterion standard in acquiring facial attractiveness ratings, they retain many shortcomings. This study's objectives were twofold: to determine whether attractiveness scores obtained from a social network site correlate with those from the traditional focus group method; and t...

We study the complexity of bribery in a network-based rating system, where individuals are connected in a social network and an attacker, typically a service provider, can influence their rating and increase the overall profit. We derive a number of algorithmic properties of this framework, in particular we show that establishing the existence of an optimal manipulation strategy for the attacke...

In this project, we attempt to predict the rating a user will give to a restaurant listed on Yelp using Yelp’s Challenge Dataset. Being able to predict the rating a user assigns to a restaurant is helpful when trying to build better recommendation systems on Yelp. We approach the problem from a social network analysis perspective by incorporating Yelp user-user friendship networks in our predic...

In this paper, we present a novel approach to reestimate the risk level of prescribers and consumers (doctors and patients) that were previously evaluated by various independent Risk Analysis Systems (RAS). This is achieved by taking into consideration social network structure between prescribers and consumers. A mathematical model, called Asymmetrical Rating Exchange Model (AREM) is proposed t...

In this paper, we propose a user reputation model and apply it to a user-interactive question answering system. It combines the social network analysis approach and the user rating approach. Social network analysis is applied to analyze the impact of participant users’ relations to their reputations. User rating is used to acquire direct judgment of a user’s reputation based on other users’ exp...