Style-based credibility classifiers

Two classifiers were developed for detecting low-crediblity online content (such as fake news) based on writing style.:

  • using a deep neural network,
  • using stylometric features.

The code for both classifiers is available on GitHub, while their detailed description could be found in the article.


A Twitter bot detection solution for the Bots & Gender Profiling shared task organised at the PAN workshop at CLEF 2019 conference. The code could be downloaded from GitHub. More information is available in the publication.


News Style Corpus

The corpus contains 103,219 documents from 18 credible and 205 non-credible sources selected based on work of PolitiFact and Pew Research Center. The data was gathered to investigate the credibility assessment based on writing style and is available for download from GitHub. More information is available in the article.