Search Results for author: Maximilian Wich

Found 8 papers, 4 papers with code

Investigating Annotator Bias with a Graph-Based Approach

1 code implementation EMNLP (ALW) 2020 Maximilian Wich, Hala Al Kuwatly, Georg Groh

In the scope of this study, we want to investigate annotator bias — a form of bias that annotators cause due to different knowledge in regards to the task and their subjective perception.

BIG-bench Machine Learning Community Detection +1

Investigating Annotator Bias in Abusive Language Datasets

no code implementations RANLP 2021 Maximilian Wich, Christian Widmer, Gerhard Hagerer, Georg Groh

A prevalent form of bias in hate speech and abusive language datasets is annotator bias caused by the annotator’s subjective perception and the complexity of the annotation task.

Abusive Language

Introducing an Abusive Language Classification Framework for Telegram to Investigate the German Hater Community

no code implementations15 Sep 2021 Maximilian Wich, Adrian Gorniak, Tobias Eder, Daniel Bartmann, Burak Enes Çakici, Georg Groh

Since traditional social media platforms continue to ban actors spreading hate speech or other forms of abusive languages (a process known as deplatforming), these actors migrate to alternative platforms that do not moderate users content.

Abusive Language Classification +1

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