Semantic mapping reveals distinct patterns in descriptions of social relations in adults with autism spectrum disorder / Sean X. LUO in Autism Research, 9-8 (August 2016)  

Public ISBD [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 et/ou numérique 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 et/ou numérique] / 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

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