Abstract
Abusive language has been corrupting online conversations since the inception of the internet. Substantial research efforts have been put into the investigation and algorithmic resolution of the problem. Different aspects such as “cyberbullying”, “hate speech” or “profanity” have undergone ample amounts of investigation, however, often using inconsistent vocabulary such as “offensive language” or “harassment”. This led to a state of confusion within the research community. The inconsistency can be considered an inhibitor for the domain: It increases the risk of unintentional redundant work and leads to undifferentiated and thus hard to use and justifiable machine learning classifiers. To remedy this effect, this paper introduces a novel configurable, multi-view approach to define abusive language concepts.
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Notes
- 1.
With the term “Socially Unacceptable Discourse” [36] introduced another umbrella term, which, however, so far has not received a similar uptake as “Abusive Language”.
- 2.
The third iteration in the year 2019 is already scheduled [7].
- 3.
- 4.
Given the context of the paper, “language” is assumed to refer to written online comments.
- 5.
- 6.
We subsume anti-semitism, anti-muslim, and other religious utterance at this point.
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Acknowledgments
The research leading to these results received funding from the federal state of North Rhine-Westphalia and the European Regional Development Fund (EFRE.NRW 2014–2020), Project:
(No. CM-2-2-036a).
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Niemann, M., Riehle, D.M., Brunk, J., Becker, J. (2020). What Is Abusive Language?. In: Grimme, C., Preuss, M., Takes, F., Waldherr, A. (eds) Disinformation in Open Online Media. MISDOOM 2019. Lecture Notes in Computer Science(), vol 12021. Springer, Cham. https://doi.org/10.1007/978-3-030-39627-5_6
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