DemetersSon83/Quantitative-Discursive-Analysis
A tool for quantitatively measuring discursive similarity between bodies of text.
This tool helps researchers, analysts, and anyone working with large volumes of text to quickly understand how similar the core ideas and topics are between different documents. You feed it two or more texts, and it outputs a 'resonance' score from 0 to 1, indicating their discursive overlap. This is useful for comparing speeches, articles, or reports to see how closely their central themes align.
Use this if you need to quantitatively measure the conceptual similarity between two or more texts by focusing on their key noun phrases and the relationships between them.
Not ideal if you need to analyze extremely large texts quickly, as calculating the centrality of terms can be computationally intensive.
Stars
9
Forks
3
Language
Python
License
MIT
Category
Last pushed
Mar 04, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/DemetersSon83/Quantitative-Discursive-Analysis"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
ryanjgallagher/shifterator
Interpretable data visualizations for understanding how texts differ at the word level
HLasse/TextDescriptives
A Python library for calculating a large variety of metrics from text
jboynyc/textnets
Text analysis with networks.
sciknoworg/tib-sid
TIB-SID: A bilingual (English/German) dataset of library catalog records with GND subject...
harrisonpim/bookworm
:books: social networks from novels