Computational analyses of linguistic features with schizophrenic and
  autistic traits along with formal thought disorders
Takeshi Saga Hiroki Tanaka Satoshi Nakamura
[See full abstract in the pdf] Formal Thought Disorder (FTD), which is a
group of symptoms in cognition that affects language and thought, can be
observed through language. FTD is seen across such developmental or psychiatric
disorders as Autism Spectrum Disorder (ASD) or Schizophrenia, and its related
Schizotypal Personality Disorder (SPD). This paper collected a Japanese
audio-report dataset with score labels related to ASD and SPD through a
crowd-sourcing service from the general population. We measured language
characteristics with the 2nd edition of the Social Responsiveness Scale (SRS2)
and the Schizotypal Personality Questionnaire (SPQ), including an odd speech
subscale from SPQ to quantify the FTD symptoms. We investigated the following
four research questions through machine-learning-based score predictions: (RQ1)
How are schizotypal and autistic measures correlated? (RQ2) What is the most
suitable task to elicit FTD symptoms? (RQ3) Does the length of speech affect
the elicitation of FTD symptoms? (RQ4) Which features are critical for
capturing FTD symptoms? We confirmed that an FTD-related subscale, odd speech,
was significantly correlated with both the total SPQ and SRS scores, although
they themselves were not correlated significantly. Our regression analysis
indicated that longer speech about a negative memory elicited more FTD
symptoms. The ablation study confirmed the importance of function words and
both the abstract and temporal features for FTD-related odd speech estimation.
In contrast, content words were effective only in the SRS predictions, and
content words were effective only in the SPQ predictions, a result that implies
the differences between SPD-like and ASD-like symptoms. Data and programs used
in this paper can be found here:
https://sites.google.com/view/sagatake/resource.