Skip to main content
Top

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

  • 01-12-2023
  • Original Article
Published in:

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

The article delves into the phenomenon of online hate speech and emotions on Twitter, focusing on the case of Greta Thunberg's presence at the UN Climate Change Conference COP25. It highlights the use of sentiment and emotion analysis to understand the dynamics of hate speech and its association with various emotions. The study tracks tweets mentioning Thunberg during the conference, analyzing network theory, natural language processing, and regression trees to identify hate speech and its emotional triggers. The findings reveal that hate speech is not uniform across groups and is influenced by specific emotions such as disgust, anger, and sadness. The research also uncovers the role of bots and astroturfing in spreading hate speech. The article concludes by emphasizing the shift in the public debate due to Donald Trump's tweet, which sparked intense emotional reactions and inter-group confrontations.

Not a customer yet? Then find out more about our access models now:

Individual Access

Start your personal individual access now. Get instant access to more than 164,000 books and 540 journals – including PDF downloads and new releases.

Starting from 54,00 € per month!    

Get access

Access for Businesses

Utilise Springer Professional in your company and provide your employees with sound specialist knowledge. Request information about corporate access now.

Find out how Springer Professional can uplift your work!

Contact us now
Title
Online hate speech and emotions on Twitter: a case study of Greta Thunberg at the UN Climate Change Conference COP25 in 2019
Authors
Sergio Arce-García
Jesús Díaz-Campo
Belén Cambronero-Saiz
Publication date
01-12-2023
Publisher
Springer Vienna
Published in
Social Network Analysis and Mining / Issue 1/2023
Print ISSN: 1869-5450
Electronic ISSN: 1869-5469
DOI
https://doi.org/10.1007/s13278-023-01052-5
This content is only visible if you are logged in and have the appropriate permissions.

Premium Partner

    Image Credits
    Neuer Inhalt/© ITandMEDIA, Nagarro GmbH/© Nagarro GmbH, AvePoint Deutschland GmbH/© AvePoint Deutschland GmbH, AFB Gemeinnützige GmbH/© AFB Gemeinnützige GmbH, USU GmbH/© USU GmbH, Ferrari electronic AG/© Ferrari electronic AG