Is LIWC reliable, efficient, and effective for the analysis of large online datasets in forensic and security contexts?

Madison Hunter, Tim Grant
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引用次数: 0

Abstract

This article evaluates the reliability, efficiency, and effectiveness of Linguistic Inquiry and Word Count (LIWC; Boyd et al., 2022) for the analysis of a white nationalist forum. This is important because LIWC has been the computational tool of choice for scores of studies generally and many examining extremist content in a forensic or security context. Our purpose, therefore, is to understand whether LIWC can be depended upon for large-scale analyses; we initially examine this here using a small sample of posts from a set of just eight users and manually checking the program's automated codings of a subset of categories. Our results show that the LIWC coding cannot be relied upon – precision falls to as low as 49.6 % and recall as low as 41.7 % for some categories. It would be possible to engage in considerable manual correction of these results, but this undermines its purported efficiency for large datasets.
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来源期刊
Applied Corpus Linguistics
Applied Corpus Linguistics Linguistics and Language
CiteScore
1.30
自引率
0.00%
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0
审稿时长
70 days
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