Schadenfreude: Malicious Joy in Social Media Interactions

Area of Science:

• Psychology
• Computational Linguistics
• Social Media Analysis

Background:

• Schadenfreude, the pleasure derived from another's misfortune, is a complex human emotion.
• Understanding the nuances and triggers of Schadenfreude is crucial for social and psychological research.
• Social media platforms provide a rich dataset for studying expressed emotions in real-time.

Purpose of the Study:

• To develop and present a typology of Schadenfreude based on a theoretical model.
• To empirically test the proposed typology using social media comments.
• To investigate the conditions under which Schadenfreude is experienced and to explore automatic detection methods.

Main Methods:

• Development of a four-type model of Schadenfreude: Compensation, Identification, Aversion, and Injustice.
• Analysis of a corpus of 472 social media comments from Facebook, Twitter, and Instagram.
• Collection and analysis of a specific corpus on Brexit for Injustice Schadenfreude.
• Lexicometric automatic analysis of Italian comments and Notre Dame fire-related posts.

Main Results:

• The study identified four distinct types of Schadenfreude.
• Empirical testing on social media data supported the typology.
• Analysis indicated that spatial or factual closeness is not a prerequisite for experiencing Schadenfreude.
• Complex emotions like Schadenfreude can be automatically extracted from social media data.

Conclusions:

• The proposed typology offers a structured framework for understanding Schadenfreude.
• Social media provides valuable insights into the expression and experience of Schadenfreude.
• Automatic analysis techniques show promise for emotion detection in large-scale online data.