Author profiling has gained considerable relevance due to its potential applications, for instance, in forensic linguistic studies, marketing analysis, and historic/literary text authorship verification. The goal of author profiling is to automatically extract demographic traits of the author of a text, such as gender, age, native language or sexual orientation.
Our approach focuses on structure rather than lexis. Syntactic and discourse-based features combined with character-, word-, sentence- and dictionary-based features compose our feature set (which has less than 200 features).
This demo showcases the capabilities of our author profiling approach. It allows the user to input a text and it outputs several predictions, namely the most likely gender of the author, the most similar literary author of our collection and the most stylistically similar book of our collection.
To know more about the work behind this demo, refer to:
Soler Company, Juan. Feature engineering for author profiling and identification: on the relevance of syntax and discourse. 2017
To the demo is available here: https://quality-taln.upf.edu/author-profiling-demo/profiling/