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Author (up) Sergio Escalera; Xavier Baro; Jordi Vitria; Petia Radeva; Bogdan Raducanu edit   pdf
doi  openurl
  Title Social Network Extraction and Analysis Based on Multimodal Dyadic Interaction Type Journal Article
  Year 2012 Publication Sensors Abbreviated Journal SENS  
  Volume 12 Issue 2 Pages 1702-1719  
  Abstract IF=1.77 (2010)
Social interactions are a very important component in peopleís 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 Timesí Blogging Heads opinion blog.
The Social Network is represented as an oriented graph, whose directed links are determined by the Influence Model. The linksí weights are a measure of the ìinfluenceî 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.
  Corporate Author Thesis  
  Publisher Molecular Diversity Preservation International Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes MILAB; OR;HuPBA;MV Approved no  
  Call Number Admin @ si @ EBV2012 Serial 1885  
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