"What else are you worried about?" – Integrating textual responses into quantitative social science research

Open-ended questions have routinely been included in large-scale survey and panel studies, yet there is some perplexity about how to actually incorporate the answers to such questions into quantitative social science research. Tools developed recently in the domain of natural language processing offer a wide range of options for the automated analysis of such textual data, but their implementation has lagged behind. In this study, we demonstrate straightforward procedures that can be applied to process and analyze textual data for the purposes of quantitative social science research. Using more than 35,000 textual answers to the question “What else are you worried about?” from participants of the German Socio-economic Panel Study (SOEP), we (1) analyzed characteristics of respondents that determined whether they answered the open-ended question, (2) used the textual data to detect relevant topics that were reported by the respondents, and (3) linked the features of the respondents to the worries they reported in their textual data. The potential uses as well as the limitations of the automated analysis of textual data are discussed.

开放式问题已被常规应用于大规模调查与面板研究中，但如何将此类问题的应答文本融入定量社会科学研究，学界仍存在诸多困惑。近年来自然语言处理（Natural Language Processing，NLP）领域开发的工具为这类文本数据的自动化分析提供了丰富路径，但相关工具的实际落地应用仍滞后于技术发展。本研究针对定量社会科学研究需求，提出可直接用于文本数据处理与分析的简便流程。本研究使用德国社会经济面板研究（SOEP）中超过35000份针对“你还有其他担忧吗？”这一开放式问题的应答文本，完成了三项核心工作：(1) 分析影响受访者是否作答该开放式问题的个体特征；(2) 从应答文本中提取受访者提及的相关担忧主题；(3) 建立受访者个体特征与其文本中所表述的担忧之间的关联。本文同时讨论了文本数据自动化分析的潜在应用场景与局限性。