Collecting data for socially intelligent surveillance and monitoring approaches: The case of conflict in competitive conversations

One of the most recent trends in surveillance research is the application of socially aware approaches, i.e. approaches that integrate human sciences findings in order to better understand, model and predict the behaviour of people under observation. One of the key requirements for the development of such approaches is the collection of corpora that provide sufficient and reliable information about social phenomena of interest. However, the computing community still pays relatively little attention to the application of methodologies suitable for observational data collection, possibly inspired by human sciences experimental work. This paper tries to fill, at least partially, such a gap by providing an introduction to data collection techniques applied in nonverbal behaviour research. The collection of a corpus aimed at the study of conflict in conversations is used as a case study and example.