Abusive Language
45 papers with code • 0 benchmarks • 9 datasets
Benchmarks
These leaderboards are used to track progress in Abusive Language
Datasets
Most implemented papers
HateMonitors: Language Agnostic Abuse Detection in Social Media
In this paper, we present our machine learning model, HateMonitor, developed for Hate Speech and Offensive Content Identification in Indo-European Languages (HASOC), a shared task at FIRE 2019.
Demographics Should Not Be the Reason of Toxicity: Mitigating Discrimination in Text Classifications with Instance Weighting
In this paper, we formalize the unintended biases in text classification datasets as a kind of selection bias from the non-discrimination distribution to the discrimination distribution.
Aggression and Misogyny Detection using BERT: A Multi-Task Approach
In recent times, the focus of the NLP community has increased towards offensive language, aggression, and hate-speech detection. This paper presents our system for TRAC-2 shared task on {``}Aggression Identification{''} (sub-task A) and {``}Misogynistic Aggression Identification{''} (sub-task B).
Intersectional Bias in Hate Speech and Abusive Language Datasets
Algorithms are widely applied to detect hate speech and abusive language in social media.
Examining Racial Bias in an Online Abuse Corpus with Structural Topic Modeling
We then use structural topic modeling to examine the content of the tweets and how the prevalence of different topics is related to both abusiveness annotation and dialect prediction.
Detect All Abuse! Toward Universal Abusive Language Detection Models
Online abusive language detection (ALD) has become a societal issue of increasing importance in recent years.
HateBERT: Retraining BERT for Abusive Language Detection in English
In this paper, we introduce HateBERT, a re-trained BERT model for abusive language detection in English.
"Nice Try, Kiddo": Investigating Ad Hominems in Dialogue Responses
Ad hominem attacks are those that target some feature of a person's character instead of the position the person is maintaining.
A study of text representations in Hate Speech Detection
The pervasiveness of the Internet and social media have enabled the rapid and anonymous spread of Hate Speech content on microblogging platforms such as Twitter.
Abuse is Contextual, What about NLP? The Role of Context in Abusive Language Annotation and Detection
We first re-annotate part of a widely used dataset for abusive language detection in English in two conditions, i. e. with and without context.