论文标题
为心理学自然语言处理构建测试床
Constructing a Testbed for Psychometric Natural Language Processing
论文作者
论文摘要
能力，态度，看法和信念的心理测量方法对于理解各种情况下的用户行为至关重要，包括健康，安全，电子商务和金融。传统上，使用基于调查的方法测量并收集了心理测量维度。从用户生成的文本中推断出这种结构可以为及时，不引人注目的收集和分析提供机会。在本文中，我们描述了为心理学自然语言处理（NLP）构建语料库的努力。我们讨论了我们的多步骤过程，以使用户文本与他们的基于调查的响应项目保持一致，并概述最终的测试床，其中包括基于调查的心理测量指标以及来自8500多名受访者的用户生成的文本。我们报告有关使用文本对用户的调查响应标签进行分类/预测的初步结果。我们还讨论了我们的工作的重要含义，以及对未来心理测试NLP研究的测试。
Psychometric measures of ability, attitudes, perceptions, and beliefs are crucial for understanding user behaviors in various contexts including health, security, e-commerce, and finance. Traditionally, psychometric dimensions have been measured and collected using survey-based methods. Inferring such constructs from user-generated text could afford opportunities for timely, unobtrusive, collection and analysis. In this paper, we describe our efforts to construct a corpus for psychometric natural language processing (NLP). We discuss our multi-step process to align user text with their survey-based response items and provide an overview of the resulting testbed which encompasses survey-based psychometric measures and accompanying user-generated text from over 8,500 respondents. We report preliminary results on the use of the text to categorize/predict users' survey response labels. We also discuss the important implications of our work and resulting testbed for future psychometric NLP research.
