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Language Sample Analysis Framework Utilizing the Natural Language Toolkit and Social Media

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Advances in Human Factors and Ergonomics in Healthcare

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 482))

Abstract

In this paper we present the Analysis of Social Discourse Framework (ASDF), which utilizes the Natural Language Toolkit [1] (NLTK 3.0 documentation. http://www.nltk.org) to analyze language samples from children on the Autism Spectrum. For those whose anxiety prohibits them from providing speech samples in response to guided elicitation we utilize free form social media posts to obtain the language samples. To demonstrate the value of ASDF, we present a formative case study illustrating the collection of samples via social media posts and the resulting analysis. In addition to providing metrics traditionally used in speech sample analysis, ASDF provides new metrics made possible through natural language processing. ASDF is open source so it can be extended by researchers to include additional metrics and additional means of acquiring the data associated with these metrics.

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Author information

Authors and Affiliations

  1. Modeling and Simulation, University of Central Florida, Orlando, FL, USA

    Ahmad Abualsamid

  2. Department of Computer Science, University of Central Florida, Orlando, FL, USA

    Charles E. Hughes

Authors
  1. Ahmad Abualsamid
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  2. Charles E. Hughes
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Corresponding author

Correspondence to Ahmad Abualsamid .

Editor information

Editors and Affiliations

  1. School of Industrial Engineering, Purdue University School of Industrial Engineering, West Lafayette, IN, USA

    Vincent G. Duffy

  2. Veterans Affairs U.S., Indianapolis, IN, USA

    Nancy Lightner

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Abualsamid, A., Hughes, C.E. (2017). Language Sample Analysis Framework Utilizing the Natural Language Toolkit and Social Media. In: Duffy, V., Lightner, N. (eds) Advances in Human Factors and Ergonomics in Healthcare. Advances in Intelligent Systems and Computing, vol 482. Springer, Cham. https://doi.org/10.1007/978-3-319-41652-6_41

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  • DOI: https://doi.org/10.1007/978-3-319-41652-6_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-41651-9

  • Online ISBN: 978-3-319-41652-6

  • eBook Packages: EngineeringEngineering (R0)

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