Behind Conspiracy Thinking: An In-Depth Analysis of Textual Structure and Emotional Patterns in the LOCO Dataset

Abstract

This thesis conducts a detailed analysis of the LOCO dataset, with a particular focus on exploring the complex connections between relationships among conspiracy texts, emotions, and mental disorders. Employing statistical analyses, the study examines the Forma Mentis networks derived from the LOCO dataset, alongside emotion classification based on the Plutchik wheel. The primary aim is to identify potential common patterns that distinguish conspiracies texts from mainstream narratives. This study highlights how important it is to analyse the relationship between emotions, mental health, conspiracy theories and their texts in order to get important understanding of these interrelated fields.