Abstract
Social interactions are a very important component in people’s lives. Social network analysis has become a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from multimodal dyadic interactions. For our study, we used a set of videos belonging to New York Times’ Blogging Heads opinion blog. The Social Network is represented as an oriented graph, whose directed links are determined by the Influence Model. The links’ weights are a measure of the “influence” a person has over the other. The states of the Influence Model encode automatically extracted audio/visual features from our videos using state-of-the art algorithms. Our results are reported in terms of accuracy of audio/visual data fusion for speaker segmentation and centrality measures used to characterize the extracted social network.
Highlights
Social interactions play a very important role in people’s daily lives
Most of the existing communication systems used by people nowadays, including some popular online communities (Facebook, YouTube, Flickr, Digg, Twitter), infer the social interactions based on explicit input analysis
A new paradigm has been introduced by Pentland [3], according to which, face to face social interactions can be inferred based on an implicit input analysis
Summary
Social interactions play a very important role in people’s daily lives. Whether face-to-face or electronic (via e-mails, SMS, online communities, etc.), they represent the main communication channel people use to strengthen their inter-personal ties. A new paradigm has been introduced by Pentland [3], according to which, face to face social interactions can be inferred based on an implicit input analysis. Social Network Analysis (SNA) [5,6] has been developed as a tool to model the social interactions in terms of a graph-based structure. SNA uncovers the implicit relationships between “actors” and provides understanding of the underlying social processes and behaviors It has become a widely used technique in a variety of application areas such as the WWW, organizational studies [7,8], security domain [9,10], etc.
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