ArticlePloS one2020
Social language in autism spectrum disorder: A computational analysis of sentiment and linguistic abstraction.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 59 citations in OpenAlex.
- Analysis of Autistic Adolescents' Essays Using Computer Techniques.Journal of autism and developmental disorders · 2026Article
- Altered kinship vocal dynamics in marmosets with valproic acid-induced model of autism.iScience · 2026Article
- Autistic Individuals Are Flexible with Physical and Emotion Gradable Adjectives.Behavioral sciences (Basel, Switzerland) · 2026Article
- Article
- Salience Network in Autism: preliminary results on functional connectivity analysis in resting state.European archives of psychiatry and clinical neuroscience · 2025Article
- Predicting autism from written narratives using deep neural networks.Scientific reports · 2025Article
- Pre-trained artificial intelligence language model represents pragmatic language variability central to autism and genetically related phenotypes.Autism : the international journal of research and practice · 2025Article
- Associations between Computationally Derived Parent Emotional Sentiment Scores and Child ADHD and ODD Over Time.Research on child and adolescent psychopathology · 2024Article
- Speech and language patterns in autism: Towards natural language processing as a research and clinical tool.Psychiatry research · 2024Review
- Autism Detection in Children: Integrating Machine Learning and Natural Language Processing in Narrative Analysis.Behavioral sciences (Basel, Switzerland) · 2024Article
- Implicit Grammatical Gender Representation in Italian Children with Autism without Intellectual/Language Disorder.Children (Basel, Switzerland) · 2023Article
- Deep Mobile Linguistic Therapy for Patients with ASD.International journal of environmental research and public health · 2022Article
- Detecting autism from picture book narratives using deep neural utterance embeddings.International journal of language & communication disorders · 2022Article
- Combining voice and language features improves automated autism detection.Autism research : official journal of the International Society for Autism Research · 2022Article
- Friend matters: sex differences in social language during autism diagnostic interviews.Molecular autism · 2022Article
- Year 2020 (with COVID): Observation of Scientific Literature on Clinical Natural Language Processing.Yearbook of medical informatics · 2021Review
- Diagnostic Tools for Autism Spectrum Disorders by Gender: Analysis of Current Status and Future Lines.Children (Basel, Switzerland) · 2021Review
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Individuals with autism spectrum disorder (ASD) demonstrate impairments with pragmatic (social) language, including narrative skills and conversational abilities. We aimed to quantitatively characterize narrative performance in ASD using natural language processing techniques: sentiment and language abstraction analyses based on the Linguistic Category Model. Individuals with ASD and with typical development matched for age, gender, ethnicity, and verbal and nonverbal intelligence quotients produced language samples during two standardized tasks from the Autism Diagnostic Observation Schedule, Second Edition assessment: Telling a Story from a Book and Description of a Picture. Only the narratives produced during the Book Task differed between ASD and control groups in terms of emotional polarity and language abstraction. Participants with typical development used words with positive sentiment more often in comparison to individuals with ASD. In the case of words with negative sentiment, the differences were marginally significant (participants with typical development used words with negative sentiment more often). The Book Task narratives of individuals with ASD were also characterized by a lower level of language abstraction than narratives of peers with typical development. Linguistic abstraction was strongly positively correlated with a higher number of words with emotional polarity. Neither linguistic abstraction nor emotional polarity correlated with participants' age or verbal and nonverbal IQ. The results support the promise of sentiment and language abstraction analyses as a useful tool for the quantitative, fully automated assessment of narrative abilities among individuals with ASD.
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