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Against the others! Detecting Moral Outrage in Social Media Networks

Titelangaben

Strathern, Wienke ; Schönfeld, Mirco ; Ghawi, Raji ; Pfeffer, Jürgen:
Against the others! Detecting Moral Outrage in Social Media Networks.
In: Proceedings of the 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. - The Hague, Netherlands (virtual) : IEEE/ACM , 2020

Volltext

Link zum Volltext (externe URL): Volltext

Abstract

Online firestorms on Twitter are seemingly arbitrarily occurring outrages towards people, companies, media campaigns and politicians. Moral outrages can create an excessive collective aggressiveness against one single argument, one single word, or one action of a person resulting in hateful speech. With a collective "against the others" the negative dynamics often start. Using data from Twitter, we explored the starting points of several firestorm outbreaks. As a social media platform with hundreds of millions of users interacting in real-time on topics and events all over the world, Twitter serves as a social sensor for online discussions and is known for quick and often emotional disputes. The main question we pose in this article, is whether we can detect the outbreak of a firestorm. Given 21 online firestorms on Twitter, the key questions regarding the anomaly detection are: 1) How can we detect the changing point? 2) How can we distinguish the features that cause a moral outrage? In this paper we examine these challenges developing a method to detect the point of change systematically spotting on linguistic cues of tweets. We are able to detect outbreaks of firestorms early and precisely only by applying linguistic cues. The results of our work can help detect negative dynamics and may have the potential for individuals, companies, and governments to mitigate hate in social media networks.

Weitere Angaben

Publikationsform: Aufsatz in einem Buch
Begutachteter Beitrag: Ja
Institutionen der Universität: Fakultäten > Sprach- und Literaturwissenschaftliche Fakultät
Fakultäten > Sprach- und Literaturwissenschaftliche Fakultät > Juniorprofessur Datenmodellierung und interdisziplinäre Wissensgenerierung
Fakultäten > Sprach- und Literaturwissenschaftliche Fakultät > Juniorprofessur Datenmodellierung und interdisziplinäre Wissensgenerierung > Juniorprofessur Datenmodellierung und interdisziplinäre Wissensgenerierung - Juniorprof. Dr. Mirco Schönfeld
Fakultäten
Titel an der UBT entstanden: Ja
Themengebiete aus DDC: 000 Informatik,Informationswissenschaft, allgemeine Werke > 004 Informatik
100 Philosophie und Psychologie > 150 Psychologie
400 Sprache > 410 Linguistik
Eingestellt am: 19 Okt 2020 09:02
Letzte Änderung: 10 Jan 2024 13:18
URI: https://eref.uni-bayreuth.de/id/eprint/58477