How can we help?

Set up, upload your first dataset, compare two corpora, and read the results with confidence.

Understand how tokens are counted, what limits apply to projects and datasets, and what happens when you exceed your plan’s quota.

An overview of frequency and keyness scoring in Discorra — how token counts are normalized, how keyness is calculated, and how to interpret statistical significance between corpora.

An overview of Messaging Analysis in Discorra — how pillars are defined, how gaps are visualized, and how to interpret messaging alignment between corpora.

An overview of resonance scoring in Discorra — what it means, how it’s calculated, and how to interpret overlap vs. divergence between corpora.

An overview of sentiment scoring in Discorra — how polarity is measured, how comparative scores work, and how to interpret positive, neutral, and negative distributions across corpora.

Guidelines for structuring meaningful corpus comparisons in Discorra — from dataset selection and normalization to interpreting overlap and divergence across analyses.

What resonance scoring means, how we calculate it, and how to interpret overlap vs. divergence between corpora.

A guided tour of Discorra’s analysis dashboard and the seven core tabs — what each view shows, when to use it, and what to do next.

Learn how to create workspaces, add corpora to projects, organize datasets, and archive old work in Discorra.