Analyzing Written Communication in AAC Contexts: A Statistical Perspective

Abstract

This research note focuses on some of the opportunities provided by the statistical analysis of textual data, by illustrating examples of the use of lexicon-based quantitative measures with texts within a particular context of augmentative and alternative communication. The corpus is composed of 12 essays produced by six individuals with autism and six participants without disabilities in a control group during sessions of facilitated communication. The study raises questions that can be answered thanks to the statistical methods implemented in the text analysis framework and other procedures that may be used to identify the characteristics of texts (and their writers) and compare texts (or subcorpora). The aim is to discuss strengths, weaknesses, opportunities, and threats of the approach and to highlight its connections to qualitative approaches.

Keywords::

• Textual data
• Autism
• Lexical richness
• Intertextual distance
• Correspondence analysis

Acknowledgements

The present study was included in the activities conducted within the framework of the EASIEST University Project, an interdisciplinary study involving linguistics, neuropsychiatry, psychology, sociology, statistics, and computer-aided text processing funded by the University of Padua, Italy (Bernardi, 2008). The collection of the essays analyzed in this study was coordinated by Vittoria Cristoferi Realdon, child neuropsychiatrist, and conducted in the Centro Sperimentale per i Disturbi dello Sviluppo e della Comunicazione in Padua. The present study is also included among activities conducted within the framework of GIAT, the Interdisciplinary Group on Text Analysis (www.giat.or).

Editor’s note

1. AAC conventions have not been applied here because the sentences are examples of typed text and are not being used in a communication situation.

Declaration of interest: The authors report no declarations of interest.