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

Research article in edited proceedings (conference) | Peer reviewed

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.

Details about the publication

Publishervan Duijn, Max; Preuss, Mike; Spaiser, Viktoria; Takes, Frank; Verberne, Suzan
Book titleDisinformation in Open Online Media. Second Multidisciplinary International Symposium, MISDOOM 2020, Leiden, The Netherlands, October 26–27, 2020, Proceedings
Page range122-137
Publishing companySpringer
Place of publicationCham
Title of seriesLecture Notes in Computer Science (ISSN: 0302-9743)
Volume of series12259
StatusPublished
Release year2020
Language in which the publication is writtenEnglish
Conference2nd Multidisciplinary International Symposium on Disinformation in Open Online Media, Leiden, Netherlands (Kingdom of the)
ISBN978-3-030-61841-4
DOI10.1007/978-3-030-61841-4_9
Link to the full texthttps://link.springer.com/chapter/10.1007%2F978-3-030-61841-4_9
KeywordsAbusive language; Comment moderation; Machine learning; Review

Authors from the University of Münster

Assenmacher, Dennis
Data Science: Statistics and Optimization (Statistik)
Becker, Jörg
Chair of Information Systems and Information Management (IS)
Brunk, Jens
Chair of Information Systems and Information Management (IS)
Niemann, Marco
Chair of Information Systems and Information Management (IS)
Riehle, Dennis
Chair of Information Systems and Information Management (IS)