Extracting Moods From Songs and BBC Programs Based on Emotional Context

The increasing amounts of media becoming available in converged digital broadcast and mobile broadband networks will require intelligent interfaces capable of personalizing the selection of content. Aiming to capture the mood in the content, the authors construct a semantic space based on tags, frequently used to describe emotions associated with music in the last.fm social network. Implementing Latent Semantic Analysis (LSA), they model the affective context of songs based on their lyrics, and apply a similar approach to extract moods from BBC synopsis descriptions of TV episodes using TV-Anytime atmosphere terms.