The typology is first tested on a corpus of comments drawn from three social media, Facebook, Twitter and Instagram. Then a specific corpus of comments is collected and analyzed concerning a specific case of Injustice Schadenfreude, the posts concerning Brexit, United Kingdom leaving the European Union. From the analysis, it emerges that spatial or factual closeness does not look necessary to feel Schadenfreude. Finally, a lexicometric automatic analysis is conducted on the general corpus of Italian comments collected using several hashtags and enriched by comments about the fire of Notre Dame, showing how even complex emotions like Schadenfreude can be automatically extracted from social media.
The social media have projected us into an age in which people are encouraged to express whatever they know, think, and feel. This means that not only information and opinions, but also emotions are spread all over the world net. Thus the social media become an inexhaustible mine of data to obtain information also on emotions that, despite their being quite frequent in everyday life, and often clearly displayed in the media, are not so investigated as primary emotions or other types of them.
This work focuses on the emotion of Schadenfreude, and exploits the richness of the social media as a repository of cases in which people experience and express this feeling Ellison et al. The objective of this study is to propose a model and a typology of cases of Schadenfreude so as to highlight its different facets allowing more precise studies on its sub-types.
To test the adequacy of the proposed model and the diffusion of this emotion, we exploit social media as a repository of cases of Schadenfreude, investigating how it is expressed on these platforms. Although the literature on Schadenfreude is not very rich, some studies have provided definitions and typologies of it, also investigating its expression and its neurophysiological mechanisms.
Literature on emotions highlights several differences between pure joy and Schadenfreude. An electromyographic analysis by Boecker et al.
