Using natural language processing technology for qualitative data analysis

被引:81
作者
Crowston, Kevin [1 ]
Allen, Eileen E. [1 ]
Heckman, Robert [1 ]
机构
[1] Syracuse Univ, Sch Informat Studies, Syracuse, NY 13244 USA
基金
美国国家科学基金会;
关键词
natural language processing; qualitative data analysis; coding; group maintenance;
D O I
10.1080/13645579.2011.625764
中图分类号
C [社会科学总论];
学科分类号
03 ; 0303 ;
摘要
Social researchers often apply qualitative research methods to study groups and their communications artifacts. The use of computer-mediated communications has dramatically increased the volume of text available, but coding such text requires considerable manual effort. We discuss how systems that process text in human languages (i.e. natural language processing [NLP]) might partially automate content analysis by extracting theoretical evidence. We present a case study of the use of NLP for qualitative analysis in which the NLP rules showed good performance on a number of codes. With the current level of performance, use of an NLP system could reduce the amount of text to be examined by a human coder by an order of magnitude or more, potentially increasing the speed of coding by a comparable degree. The paper is significant as it is one of the first to demonstrate the use of high-level NLP techniques for qualitative data analysis.
引用
收藏
页码:523 / 543
页数:21
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