Against the others! Detecting Moral Outrage in Social Media Networks

Title data

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 . - (ASONAM )

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Abstract in another language

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.

Further data

Item Type:	Article in a book
Refereed:	Yes
Institutions of the University:	Faculties > Faculty of Languages and Literature Faculties > Faculty of Languages and Literature > Juniorprofessur Datenmodellierung und interdisziplinäre Wissensgenerierung Faculties > Faculty of Languages and Literature > Juniorprofessur Datenmodellierung und interdisziplinäre Wissensgenerierung > Juniorprofessur Datenmodellierung und interdisziplinäre Wissensgenerierung - Juniorprof. Dr. Mirco Schönfeld Faculties
Result of work at the UBT:	Yes
DDC Subjects:	000 Computer Science, information, general works > 004 Computer science 100 Philosophy and psychology > 150 Psychology 400 Language > 410 Linguistics
Date Deposited:	19 Oct 2020 09:02
Last Modified:	19 Oct 2020 09:02
URI:	https://eref.uni-bayreuth.de/id/eprint/58477