Abusive Comments in Online Media and How to Fight Them: State of the Domain and a Call to Action
Niemann Marco, Welsing Jens, Riehle Dennis M, Brunk Jens, Assenmacher Dennis, Becker Jörg
Abstract
While abusive language in online contexts is a long-known problem, algorithmic detection and moderation support are only recently experiencing rising interest. This survey provides a structured overview of the latest academic publications in the domain. Assessed concepts include the used datasets, their language, annotation origins and quality, as well as applied machine learning approaches. It is rounded off by an assessment of meta aspects such as author collaborations and networks as well as extant funding opportunities. Despite all progress, the domain still has the potential to improve on many aspects: (international) collaboration, diversifying and increasing available datasets, careful annotations, and transparency. Furthermore, abusive language detection is a topic of high societal relevance and requires increased funding from public authorities.
Keywords
Abusive language; Comment moderation; Machine learning; Review
Cite as
Niemann, M., Welsing, J., Riehle, D. M., Brunk, J., Assenmacher, D., & Becker, J. (2020). Abusive Comments in Online Media and How to Fight Them: State of the Domain and a Call to Action. In van Duijn, , Max;, P., Mike;, S., Viktoria;, T., Frank;, V., & Suzan, (Eds.),
Disinformation in Open Online Media. Second Multidisciplinary International Symposium, MISDOOM 2020, Leiden, The Netherlands, October 26–27, 2020, Proceedings (pp. 122–137). Lecture Notes in Computer Science: Vol. 12259. Cham: Springer.
Details
Publication type
Research article in proceedings (conference)
Peer reviewed
Yes
Publication status
Published
Year
2020
Conference
2nd Multidisciplinary International Symposium on Disinformation in Open Online Media
Venue
Leiden
Book title
Disinformation in Open Online Media. Second Multidisciplinary International Symposium, MISDOOM 2020, Leiden, The Netherlands, October 26–27, 2020, Proceedings
Editor
van Duijn, Max; Preuss, Mike; Spaiser, Viktoria; Takes, Frank; Verberne, Suzan
Start page
122
End page
137
Volume
12259
Title of series
Lecture Notes in Computer Science
Publisher
Springer
Place
Cham
Language
English
ISSN
0302-9743
ISBN
978-3-030-61841-4
DOI
Full text
