Semi-Automatic Content Analysis of Qualitative Data

Yan, Jasy Liew Suet; McCracken, Nancy; Crowston, Kevin

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https://hdl.handle.net/2142/47333 Copy

Description

Title

Semi-Automatic Content Analysis of Qualitative Data

Author(s)

• Yan, Jasy Liew Suet
• McCracken, Nancy
• Crowston, Kevin

Issue Date

2014-03-01

Keyword(s)

• natural language processing
• qualitative research methods
• semi-automatic content analysis
• machine learning
• active learning

Abstract

Qualitative content analysis is commonly used by social scientists to understand the practices of the groups they study, but it is often infeasible to manually code a large text corpus within a reasonable time frame and budget. To address this problem, we are building a software tool to assist social scientists performing content analysis. We present our semi-automatic system that leverages natural language processing (NLP) and machine learning (ML) techniques for initial automatic coding, which human coders then review and correct. Through active learning, these human-verified annotations are subsequently used to train a higher performing model for machine annotation. We discuss design strategies adopted to optimize the system performance.

Publisher

iSchools

Series/Report Name or Number

iConference 2014 Proceedings

Type of Resource

text

Language

english

Permalink

http://hdl.handle.net/2142/47333

DOI

https://doi.org/10.9776/14399

Copyright and License Information

Copyright 2014 is held by the authors of individual items in the proceedings. Copyright permissions, when appropriate, must be obtained directly from the authors.

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