SCORES: A Clustering Tool for Free-Text Responses

Abstract

Free-text responses are a crucial part of psychological research, enabling participants to respond without bias toward a predefined set of answers. Unfortunately, many established methods for analyzing such responses require extensive manual coding, which is time- and resource-intensive. To address this issue, automatic-processing methods based on word embeddings and clustering techniques have been proposed. In this article, we introduce SCORES (Semantic Clustering of Open Responses via Embedding Similarity), a user-friendly, graphical tool that makes such automatic methods easy to use and understand for psychological researchers.