  This research investigates the effective incorporation of the human factor
and user perception in text-based interactive media. In such contexts, the
reliability of user texts is often compromised by behavioural and emotional
dimensions. To this end, several attempts have been made in the state of the
art, to introduce psychological approaches in such systems, including
computational psycholinguistics, personality traits and cognitive psychology
methods.
  In contrast, our method is fundamentally different since we employ a
psychoanalysis-based approach; in particular, we use the notion of Lacanian
discourse types, to capture and deeply understand real (possibly elusive)
characteristics, qualities and contents of texts, and evaluate their
reliability. As far as we know, this is the first time computational methods
are systematically combined with psychoanalysis. We believe such psychoanalytic
framework is fundamentally more effective than standard methods, since it
addresses deeper, quite primitive elements of human personality, behaviour and
expression which usually escape methods functioning at "higher", conscious
layers. In fact, this research is a first attempt to form a new paradigm of
psychoanalysis-driven interactive technologies, with broader impact and diverse
applications.
  To exemplify this generic approach, we apply it to the case-study of fake
news detection; we first demonstrate certain limitations of the well-known
Myers-Briggs Type Indicator (MBTI) personality type method, and then propose
and evaluate our new method of analysing user texts and detecting fake news
based on the Lacanian discourses psychoanalytic approach.
