Social Behaviour Understanding using Deep Neural Networks: Development
  of Social Intelligence Systems
  With the rapid development in artificial intelligence, social computing has
evolved beyond social informatics toward the birth of social intelligence
systems. This paper, therefore, takes initiatives to propose a social behaviour
understanding framework with the use of deep neural networks for social and
behavioural analysis. The integration of information fusion, person and object
detection, social signal understanding, behaviour understanding, and context
understanding plays a harmonious role to elicit social behaviours. Three
systems, including depression detection, activity recognition and cognitive
impairment screening, are developed to evidently demonstrate the importance of
social intelligence. The study considerably contributes to the cumulative
development of social computing and health informatics. It also provides a
number of implications for academic bodies, healthcare practitioners, and
developers of socially intelligent agents.
