2016/08/10 by Mohamed M. Mostafa, Mohamed Mostafa, Tom Crick +6
Computer Science · Physics and Astronomy · Psychology · #Complex Network Analysis Techniques #Computers and Society (cs.CY) #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Personality Traits and Psychology #Sentiment Analysis and Opinion Mining #cs.CY #cs.HC
paper · pdf · doi:10.48550/arxiv.1608.03061
Full paper submitted to the 36th SGAI International Conference on Artificial Intelligence (AI-2016); 15 pages, LaTeX
arxiv created 2016/08/10 · openalex publication_date 2016/08/10 · arxiv updated 2016/08/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.