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Social Network Analysis and Mining
Erschienen in: Social Network Analysis and Mining 1/2023

01.12.2023 | Original Article

Online hate speech and emotions on Twitter: a case study of Greta Thunberg at the UN Climate Change Conference COP25 in 2019

verfasst von: Sergio Arce-García, Jesús Díaz-Campo, Belén Cambronero-Saiz

Erschienen in: Social Network Analysis and Mining | Ausgabe 1/2023

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Abstract

The presence of environmental activist Greta Thunberg at the UN Climate Change Conference COP25 in 2019 prompted reactions on social media, which grew exponentially after she was named Time Magazine's Person of the Year 2019 and even more so after then-president of the United States Donald Trump tweeted his reaction to her accolade. An analysis of 1,395,054 tweets gathered between November and December 2019 through R, network theory techniques, machine learning and natural language processing showed how messages sparking hatred and intense emotions generate posts, mainly negative ones that subsequently serve as catalysts. The results also demonstrate the relevance of the bubble filter and echo chamber theories and the fact that hate springs from a range of sentiments depending on each participant group.
Vorheriger Artikel Towards more robust hate speech detection: using social context and user data
Nächster Artikel Go vegan! digital influence and social media use in the purchase intention of vegan products in the cosmetics industry

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Metadaten
Titel
Online hate speech and emotions on Twitter: a case study of Greta Thunberg at the UN Climate Change Conference COP25 in 2019
verfasst von
Sergio Arce-García
Jesús Díaz-Campo
Belén Cambronero-Saiz
Publikationsdatum
01.12.2023
Verlag
Springer Vienna
Erschienen in
Social Network Analysis and Mining / Ausgabe 1/2023
Print ISSN: 1869-5450
Elektronische ISSN: 1869-5469
DOI
https://doi.org/10.1007/s13278-023-01052-5

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