Predicting the conflict level in television political debates: An approach based on crowdsourcing, nonverbal communication and Gaussian processes

One of the most recent trends in multimedia indexing is to represent data in terms of the social and psychological phenomena that users perceive. In such a perspective this article proposes an approach for the automatic detection of conflict level in television political debates. The proposed approach includes the use of crowdsourcing techniques for modeling the perception of data consumers, the extraction of (language independent) nonverbal behavioral cues and the application of regression techniques based on Gaussian Processes. The experiments have been performed over 1430 clips of 30 seconds extracted from 45 political debates (roughly 12 hours of material). The results show that a correlation up to 0.8 can be achieved between the actual and predicted conflict level.