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Modeling Emotional Context from Latent Semantics by Michael Kai Petersen; Andrius Butkus is a scholarly article available to read on EtoBox.

What is Modeling Emotional Context from Latent Semantics about?

In order to extract the atmosphere in media, we model the latent semantics of TV synopses and affective terms as patterns of emotional components. Using a selection of affective last.fm tags and TV-Anytime atmosphere terms as emotional buoys, we apply LSA latent semantic analysis to represent the correlation of terms and descriptions in a vector space that reflects the emotional context. Analyzing the resulting patterns of affective components, we propose that this approach could be applied to automatically generate affective user preferences based on synopsis, subtitles or other textual representations associated with media.

Author

Michael Kai Petersen; Andrius Butkus

Publisher

ACM

Published

2008

Language

EN