[article] 
inAutism Research > 9-8 (August 2016) . - p.846-853

Titre :	Semantic mapping reveals distinct patterns in descriptions of social relations in adults with autism spectrum disorder
Type de document :	texte imprimé
Auteurs :	Sean X. LUO, Auteur ; Jacqueline A. SHINALL, Auteur ; Bradley S. PETERSON, Auteur ; Andrew J. GERBER, Auteur
Article en page(s) :	p.846-853
Langues :	Anglais (eng)
Mots-clés :	machine learning  semantic web  autism spectrum disorder  latent semantic indexing  classification  small-world network
Index. décimale :	PER Périodiques
Résumé :	Adults with autism spectrum disorder (ASD) may describe other individuals differently compared with typical adults. In this study, we first asked participants to describe closely related individuals such as parents and close friends with 10 positive and 10 negative characteristics. We then used standard natural language processing methods to digitize and visualize these descriptions. The complex patterns of these descriptive sentences exhibited a difference in semantic space between individuals with ASD and control participants. Machine learning algorithms were able to automatically detect and discriminate between these two groups. Furthermore, we showed that these descriptive sentences from adults with ASD exhibited fewer connections as defined by word–word co-occurrences in descriptions, and these connections in words formed a less “small-world” like network. Autism Res 2016, 9: 846–853. © 2015
En ligne :	http://dx.doi.org/10.1002/aur.1581
Permalink :	https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=293

[article] Semantic mapping reveals distinct patterns in descriptions of social relations in adults with autism spectrum disorder [texte imprimé] / Sean X. LUO, Auteur ; Jacqueline A. SHINALL, Auteur ; Bradley S. PETERSON, Auteur ; Andrew J. GERBER, Auteur . - p.846-853.
Langues : Anglais (eng)
in Autism Research > 9-8 (August 2016) . - p.846-853

Mots-clés :	machine learning  semantic web  autism spectrum disorder  latent semantic indexing  classification  small-world network
Index. décimale :	PER Périodiques
Résumé :	Adults with autism spectrum disorder (ASD) may describe other individuals differently compared with typical adults. In this study, we first asked participants to describe closely related individuals such as parents and close friends with 10 positive and 10 negative characteristics. We then used standard natural language processing methods to digitize and visualize these descriptions. The complex patterns of these descriptive sentences exhibited a difference in semantic space between individuals with ASD and control participants. Machine learning algorithms were able to automatically detect and discriminate between these two groups. Furthermore, we showed that these descriptive sentences from adults with ASD exhibited fewer connections as defined by word–word co-occurrences in descriptions, and these connections in words formed a less “small-world” like network. Autism Res 2016, 9: 846–853. © 2015
En ligne :	http://dx.doi.org/10.1002/aur.1581
Permalink :	https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=293