[âi¬ý¹q¼v¤àªr Rolenet: Movie Analysis from the Perspective of Social Network Table of Contents

We present a brave new way to analyze movie content, from the perspective of the relationships between roles rather than low-level audiovisual features. Interactions between roles in a movie resemble human behaviors in a society. Roles’ actions lead the story and make viewers understand what directors want to present. In this thesis, we introduce the idea of social network analysis to model the relationships of actors/actresses as a network, called RoleNet. Through analyzing this network, the proposed approach automatically determines the leading roles and the communities embedded in movies. We also describe an implementation framework to realize the proposed model. Based on RoleNet, we provide some insights to facilitate more semantic extensions, which go beyond the capabilities of pure feature-based methods. Its believed that the proposed idea establishes a new way to perform movie content analysis.