The Semantic Scale Network: An Online Tool to Detect Semantic Overlap of Psychological Scales and Prevent Scale Redundancies
The Semantic Scale Network: An Online Tool to Detect Semantic Overlap of Psychological Scales and Prevent Scale Redundancies
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DOI：
10.1037/met0000244
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发表时间：
2020-06-01
影响因子：
7
通讯作者：
Pit, Ilse L.
中科院分区：
文献类型：
--
作者：
Rosenbusch, Hannes;Wanders, Florian;Pit, Ilse L.
心理测量和理论正受到新结构和尺度不断扩散的影响。由于新量表往往具有冗余的性质，心理科学正在与任意测量、结构稀释和研究小组之间的脱节作斗争。为了解决这些问题，我们引入了一个易于使用的在线应用程序：语义尺度网络。该应用程序的目的是通过潜在语义分析自动检测尺度之间的语义重叠。作者和审阅者可以将新量表的项目输入到应用程序中，并接收与应用程序语料库中的相关量表的语义重叠的量化。与传统的尺度重叠评估相反，该应用程序可以支持专家对尺度冗余的判断，而无需访问经验数据或了解每个潜在相关的尺度。在简要介绍了文本中语义相似性的度量之后，我们介绍了语义尺度网络，并提供了解释其输出的最佳实践。“幸福”或“智力”）和尺度（例如，为衡量这些结构而开发的问卷）。由于新量表往往具有冗余的性质，心理科学正在与任意测量、结构稀释和研究小组之间的脱节作斗争。为了解决这些问题，我们引入了一个易于使用的在线应用程序：语义尺度网络。该应用程序的目的是通过一种称为潜在语义分析的基于语言的算法自动检测尺度之间的语义重叠。心理学研究的作者和评论者可以将新量表的问题输入到应用中，并且接收与应用的语料库中的相关量表的语义重叠的量化（即，收集书面材料）。与传统的尺度重叠评估相反，该应用程序可以支持专家对尺度冗余的判断，而无需访问经验数据（例如，对问卷的回答）或对每个潜在相关量表的认识。在简要介绍了文本中语义相似性的度量之后，我们介绍了语义尺度网络，并提供了解释其输出的最佳实践。
Psychological measurement and theory are afflicted with an ongoing proliferation of new constructs and scales. Given the often redundant nature of new scales, psychological science is struggling with arbitrary measurement, construct dilution, and disconnection between research groups. To address these issues, we introduce an easy-to-use online application: the Semantic Scale Network. The purpose of this application is to automatically detect semantic overlap between scales through latent semantic analysis. Authors and reviewers can enter the items of a new scale into the application, and receive quantifications of semantic overlap with related scales in the application's corpus. Contrary to traditional assessments of scale overlap, the application can support expert judgments on scale redundancy without access to empirical data or awareness of every potentially related scale. After a brief introduction to measures of semantic similarity in texts, we introduce the Semantic Scale Network and provide best practices for interpreting its outputs.Translational AbstractPsychological measurement and theory are afflicted with an ongoing proliferation of new constructs (e.g., "happiness" or "intelligence") and scales (e.g., questionnaires developed to measure these constructs). Given the often redundant nature of new scales, psychological science is struggling with arbitrary measurement, construct dilution, and disconnection between research groups. To address these issues, we introduce an easy-to-use online application: the Semantic Scale Network. The purpose of this application is to automatically detect semantic overlap between scales through a language-based algorithm called latent semantic analysis. Authors and reviewers of psychological research can enter the questions of a new scale into the application, and receive quantifications of semantic overlap with related scales in the application's corpus (i.e., collection of written texts). Contrary to traditional assessments of scale overlap, the application can support expert judgments on scale redundancy without access to empirical data (e.g., answers to the questionnaires) or awareness of every potentially related scale. After a brief introduction to measures of semantic similarity in texts, we introduce the Semantic Scale Network and provide best practices for interpreting its outputs.