Weston Sara J, Cox Keith S, Condon David M, Jackson Joshua J
Washington University in St. Louis.
Medical University of South Carolina.
J Pers. 2016 Oct;84(5):594-606. doi: 10.1111/jopy.12183. Epub 2015 Jun 13.
The majority of life narrative research is performed using trained human coders. In contrast, automated linguistic analysis is oft employed in the study of verbal behaviors. These two methodological approaches are directly compared to determine the utility of automated linguistic analysis for the study of life narratives. In a study of in-person interviews (N = 158) and a second study of life stories collected online (N = 242), redemption scores are compared to the output of the Linguistic Inquiry and Word Count (Pennebaker, Francis & Booth, 2001). Additionally, patterns of language are found using exploratory principal components analysis. In both studies, redemption scores are modestly correlated with some LIWC categories and unassociated with the components. Patterns of language do not replicate across samples, indicating that the structure of language does not extend to a broader population. Redemption scores and linguistic components are independent predictors of life satisfaction up to 3 years later. These studies converge on the finding that human-coded redemption and automated linguistic analysis are complementary and nonredundant methods of analyzing life narratives, and considerations for the study of life narratives are discussed.
大多数生活叙事研究是由经过培训的人工编码员进行的。相比之下，自动语言分析常用于言语行为研究。直接比较这两种方法，以确定自动语言分析在生活叙事研究中的效用。在一项面对面访谈研究（N = 158）和另一项在线收集生活故事的研究（N = 242）中，将救赎分数与语言查询与字数统计软件（Pennebaker、Francis和Booth，2001）的输出结果进行比较。此外，使用探索性主成分分析来发现语言模式。在两项研究中，救赎分数与一些语言查询与字数统计软件的类别存在适度相关性，与各成分无关。语言模式在不同样本中无法复制，这表明语言结构并不适用于更广泛的人群。救赎分数和语言成分是长达3年后生活满意度的独立预测因素。这些研究得出的结论是，人工编码的救赎分析和自动语言分析是分析生活叙事的互补且非冗余的方法，并讨论了生活叙事研究的相关考量因素。
