大数据与计算工具的出现,为社会学研究中大规模文本资源 的利用带来了新的可能。 近年来,文化社会学、科学社会学以及经济社 会学的研究表明,计算文本分析可用于理论构建与检验。 本文首先回顾 了社会学中计算机辅助文本分析的历史,然后探讨了当代研究中使用的 五种计算方法。 通过典型研究案例,本文展示了词典法、语义和网络文 本分析、语言表示、无监督文本聚类分析和监督文本分类如何帮助社会 学家完成不同的分析任务。 在介绍最新方法论进展的基础上,本文总结 了使用大规模数据集与计算方法推导文本复杂含义的若干重要启示。 最后,作者呼吁来自不同方法论传统的研究者在采用文本挖掘工具时, 仍应谨记从传统数据与方法中汲取的经验教训。

The emergence of big data and computational tools has introduced new possibilities for using large-scale textual sources in sociological research. Recent work in sociology of culture, science, and economic sociology has shown how computational text analysis can be used in theory building and testing. This review starts with an introduction of the history of computer-assisted text analysis in sociology and then proceeds to discuss five families of computational methods used in contemporary research. Using exemplary studies, it shows how dictionary methods, semantic and network analysis tools, language models, unsupervised, and supervised machine learning can assist sociologists with different analytical tasks. After presenting recent methodological developments, this review summarizes several important implications of using large datasets and computational methods to infer complex meaning in texts. Finally, it calls researchers from different methodological traditions to adopt text mining tools while remaining mindful of lessons learned from working with conventional data and methods.