抄録
This study introduces the Web-Based Corpus Analyzer (WBCA), a browser-based corpus analysis tool designed to support transparent and reproducible corpus research through explicit user-controlled operations. Using a publicly available demo corpus, the study illustrates how WBCA integrates core corpus-linguistic functions—Keyword-in-Context (KWIC), collocation analysis, high-frequency feature extraction, and keyness analysis—within a unified, KWIC-centered workflow. The system supports both plain-text and linguistically annotated corpora while preserving identical analytical logic across modes. All computations are executed locally in the web browser, ensuring data privacy and enabling interactive exploration through filters, sorting, and contextual highlighting. The focus is placed on documenting the analytical workflow, statistical measures, and interface design of the initial public release of WBCA rather than on linguistic interpretation.
