Carregant...
Fitxers
Tipus de document
ArticleVersió
Versió publicadaData de publicació
Llicència de publicació
Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/53330
Social network extraction and analysis based on multimodal dyadic interaction
Títol de la revista
Director/Tutor
ISSN de la revista
Títol del volum
Recurs relacionat
Resum
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.
Matèries (anglès)
Citació
Citació
ESCALERA GUERRERO, Sergio, BARÓ I SOLÉ, Xavier, VITRIÀ I MARCA, Jordi, RADEVA, Petia, RADUCANU, Bogdan. Social network extraction and analysis based on multimodal dyadic interaction. _Sensors_. 2012. Vol. 12, núm. 2, pàgs. 1702-1719. [consulta: 24 de gener de 2026]. ISSN: 1424-8220. [Disponible a: https://hdl.handle.net/2445/53330]