This section addresses imbalanced datasets and generic differences in QAnon text analysis, creating large and controlled subcorpora for machine-learning models.

This section highlights the challenges of building a reliable text corpus for QAnon authorship analysis due to deleted accounts and limited archival data.

Machine learning identifies linguistic patterns in QAnon texts, suggesting key authors like Ron W. and Paul F., and uncovering distinct writing styles.