Corpus sense 2: a re-engineered platform for corpus exploration and analysis

Corpus Sense is a web application for content and discourse analysis designed to make advanced corpus exploration accessible to a broad range of user profiles, from corpus linguists to social scientists with no technical background. The original version, described in Moreno-Ortiz (2025), combined traditional corpus analysis methods with natural language processing and AI-assisted functionalities: keyword extraction, named entity recognition, semantic search, topic modelling with labels generated by a large language model (LLM), and LLM-generated insights. This paper presents version 2.0, a major release that re-engineers the platform and extends its analytical tool set. The monolithic implementation of the first version has been replaced by a modular platform with asynchronous background processing: analytics become available as soon as linguistic parsing completes, long-running analyses no longer tie the user to an open browser tab, and new tools can be added without structural rework. On this foundation, version 2.0 delivers the functionalities identified as priorities in the original paper: grammatical collocation analysis with an interactive navigator, n-gram extraction with C-value scoring and interactive curation, transformer-based sentiment and emotion classification with corpus trajectories, and metadata-based subcorpora, together with corpus-wide dispersion and evenness statistics and a redesigned WordMap visualisation. Every tool from the first version has been revised. The paper describes the new architecture, the revised and new tools, and the platform’s AI-assisted features; it situates the collocation and n-gram tools against Sketch Engine, AntConc, WordSmith Tools, CQPweb and LancsBox, including an empirical comparison, and closes with a roadmap of further modules.