J Res Pers. 2008 Feb;42(1):96-132. doi: 10.1016/j.jrp.2007.04.006.
A new method for extracting common themes from written text is introduced and applied to 1,165 open-ended self-descriptive narratives. Drawing on a lexical approach to personality, the most commonly-used adjectives within narratives written by college students were identified using computerized text analytic tools. A factor analysis on the use of these adjectives in the self-descriptions produced a 7-factor solution consisting of psychologically meaningful dimensions. Some dimensions were unipolar (e.g., Negativity factor, wherein most loaded items were negatively valenced adjectives); others were dimensional in that semantically opposite words clustered together (e.g., Sociability factor, wherein terms such as shy, outgoing, reserved, and loud all loaded in the same direction). The factors exhibited modest reliability across different types of writ writing samples and were correlated with self-reports and behaviors consistent with the dimensions. Similar analyses with additional content words (adjectives, adverbs, nouns, and verbs) yielded additional psychological dimensions associated with physical appearance, school, relationships, etc. in which people contextualize their self-concepts. The results suggest that the meaning extraction method is a promising strategy that determines the dimensions along which people think about themselves.
本文介绍了一种从书面文本中提取共同主题的新方法，并将其应用于1165篇开放式自我描述性叙事中。基于词汇学的人格研究方法，利用计算机文本分析工具识别大学生所写叙事中最常用的形容词。对这些形容词在自我描述中的使用情况进行因子分析，得到了一个由七个心理意义维度组成的解决方案。有些维度是单极的（例如消极性因子，其中大多数载荷项都是负价形容词）；其他维度则是双向的，即语义相反的词聚集在一起（例如社交性因子，其中害羞、外向、矜持和开朗等词都朝同一方向载荷）。这些因子在不同类型的写作样本中表现出适度的可靠性，并与自我报告以及与这些维度一致的行为相关。对其他内容词（形容词、副词、名词和动词）进行类似分析，得出了与外貌、学校、人际关系等相关的额外心理维度，人们在这些维度中构建自己的自我概念。结果表明，意义提取方法是一种很有前景的策略，它能确定人们思考自身的维度。
