Augmenting Multi-Party Face-to-Face Interactions Amongst Strangers with User Generated Content

Face-to-Face Sharing with Strangers and Altruistic Punishment of Acquaintances for Strangers: Young Adolescents Exhibit Greater Altruism than Adults

Young adolescents are generally considered to be self-absorbed. Studies indicate that they lack relevant general cognitive abilities, such as impulse control, that mature in early adulthood. However, their idealism may cause them to be more intolerant of unfair treatment to others and thus result in their engaging in more altruistic behavior. The present study aimed to clarify whether young ado...

Analysing Face to Face Computer-mediated Interactions

Detailed analysis of face to face computer mediated interactions implies a study of a corpus composed of the interaction traces produced by the collaborative tool and video and audio recordings. Because of their separate nature, it is frequently difficult to perform this joint analysis. In order to facilitate such analyses we propose a model for describing corpora composed of sources from diffe...

Learning to Recommend with User Generated Content

In the era of Web 2.0, user generated content (UGC), such as social tag and user review, widely exists on the Internet. However, in recommender systems, most of existing related works only study single kind of UGC in each paper, and different types of UGC are utilized in different ways. This paper proposes a unified way to use different types of UGC to improve the prediction accuracy for recomm...

Time-varying networks approach to face-to-face empirical interactions

F2FCrowds: Planning Agent Movements to Enable Face-to-Face Interactions

We present an approach for multi-agent navigation that facilitates face-to-face interaction in virtual crowds. We describe a model of approach behavior for virtual agents that includes a novel interaction velocity prediction (IVP) algorithm. This algorithm is combined with human body motion synthesis constraints and facial actions to improve the behavioral realism of virtual agents. We combine ...