Resumen de Multilingual Affect Polarity and Valence Prediction in Metaphors
Understanding metaphor rich texts like "Her lawyer is a shark", "Time is money”, “We need to construct a strong argument” and the affect associated with them is a challenging problem, which has been of interest to the research community for a long time. One crucial challenge is to build an automated system that can identify the polarity and valence associated with metaphors and create multilingual platform for that. In this talk, I will introduce the task of multilingual sentiment analysis of metaphors and will present novel algorithms that integrate affective, perceptual and social processes with stylistic and lexical information. Finally, by running evaluations on datasets in English, Spanish, Farsi and Russian, I will show that the method is portable and works equally well when applied to different languages.
