🕸️ Free tool to turn your texts into semantic graphs

Use it directly by selecting the data to be analyzed:


... or read below about what it does, and how it works:

Semantic networks - turn your texts into graphs

Levallois, C., Clithero, J. A., Wouters, P., Smidts, A., & Huettel, S. A. (2012). Translating upwards: linking the neural and social sciences via neuroeconomics. Nature Reviews Neuroscience, 13(11), 789-797.

Import your data, get the results: an example

list of options to import texts

The function takes one parameter (what is the language of the text?) and runs with one click:

how to import a text and turn it into a network

Read this simple and helpful tutorial

tutorial by Veronica Espinoza on transforming a text into a semantic network

The model - short description

The function identifies pairs of terms in each line of the text. These pairs are called co-occurrences. Aggregating all pairs of terms and selecting the most frequent ones, a network of terms is constructed where any two terms are connected if they often appear together in the text.

The model - long description

Tips and tricks to get insights from a semantic network

When your text is structured, with lists of items