Analysis of Autistic Adolescents' Essays Using Computer Techniques

Challenges associated with narrative discourse remain consistently observable across the entire spectrum of autism. We analyzed written narratives by autistic and non-autistic adolescents and aimed to investigate narrative writing using quantitative computational methods.

We employed Natural Language Processing techniques to compare 333 essays from students in the final eighth grade of primary school: 195 written by autistic and 138 by non-autistic participants.

Autistic students used words with a positive emotional polarity statistically less frequently (p < .001), and their stories were less abstract (p < .001) than those written by peers from the non-autistic group. However, autistic adolescents wrote more complex stories in terms of readability than participants from the non-autistic group (p < .001). The writing competencies assessed by teachers did not differ significantly between the two groups.

Findings suggest that written narratives by autistic individuals may exhibit characteristics similar to those detected by computational methods in spoken narratives. Collecting data from national exams and its potential usefulness in distinguishing autistic individuals could pave the way for future large-scale and cost-effective epidemiological studies on autism.