  Understanding complex user behaviour under various conditions, scenarios and
journeys can be fundamental to the improvement of the user-experience for a
given system. Predictive models of user reactions, responses -- and in
particular, emotions -- can aid in the design of more intuitive and usable
systems. Building on this theme, the preliminary research presented in this
paper correlates events and interactions in an online social network against
user behaviour, focusing on personality traits. Emotional context and tone is
analysed and modelled based on varying types of sentiments that users express
in their language using the IBM Watson Developer Cloud tools. The data
collected in this study thus provides further evidence towards supporting the
hypothesis that analysing and modelling emotions, sentiments and personality
traits provides valuable insight into improving the user experience of complex
social computer systems.
