Mental disorders over time: a dictionary-based approach to the analysis of knowledge domains

Kouper, Inna; Zoss, Angela; Edelblute, Trevor; Boyles, Michael; Ekbia, Hamid

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https://hdl.handle.net/2142/89299 Copy

Description

Title

Mental disorders over time: a dictionary-based approach to the analysis of knowledge domains

Author(s)

Kouper, Inna; Zoss, Angela; Edelblute, Trevor; Boyles, Michael; Ekbia, Hamid

Issue Date

2016-03-15

Keyword(s)

• mental disorders
• domain analysis
• visual analytics
• knowledge domains
• concept history

Abstract

Every decade brings changes in the perceptions of normal in mental health, as well as in how abnormal is labeled, understood, and dealt with. Neurosis, hysteria, and homosexuality are just a few examples of such changes. The shifts in terminology and classifications reflect our continuous struggle with social representations and treatment of the “other.” How could we best understand mental illness categorizations and become aware of their changes over time? In this paper, we seek to address this and other questions by applying an automated dictionary-based classification approach to the analysis of relevant research literature over time. We propose to examine the domain of mental health literature with an iterative workflow that combines large-scale data, an automated classifier, and visual analytics. We report on the early results of our analysis and discuss challenges and opportunities of using the workflow in domain analysis over time.

Publisher

iSchools

Series/Report Name or Number

IConference 2016 Proceedings

Type of Resource

text

Language

eng

Permalink

http://hdl.handle.net/2142/89299

DOI

https://doi.org/10.9776/16303

Copyright and License Information

Copyright 2016 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.

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