[HTML][HTML] A survey on hate speech detection and sentiment analysis using machine learning and deep learning models
In today's digital era, the rise of hate speech has emerged as a critical concern, driven by the
rapid information-sharing capabilities of social media platforms and online communities. As …
rapid information-sharing capabilities of social media platforms and online communities. As …
You only prompt once: On the capabilities of prompt learning on large language models to tackle toxic content
The spread of toxic content online is an important problem that has adverse effects on user
experience online and in our society at large. Motivated by the importance and impact of the …
experience online and in our society at large. Motivated by the importance and impact of the …
Overview of the hasoc subtrack at fire 2021: Hate speech and offensive content identification in english and indo-aryan languages and conversational hate speech
The HASOC track is dedicated to the evaluation of technology for finding Offensive
Language and Hate Speech. HASOC is creating a multilingual data corpus mainly for …
Language and Hate Speech. HASOC is creating a multilingual data corpus mainly for …
Overview of the clef–2022 checkthat! lab on fighting the covid-19 infodemic and fake news detection
We describe the fifth edition of the CheckThat! lab, part of the 2022 Conference and Labs of
the Evaluation Forum (CLEF). The lab evaluates technology supporting tasks related to …
the Evaluation Forum (CLEF). The lab evaluates technology supporting tasks related to …
Overview of the GermEval 2021 shared task on the identification of toxic, engaging, and fact-claiming comments
We present the GermEval 2021 shared task on the identification of toxic, engaging, and fact-
claiming comments. This shared task comprises three binary classification subtasks with the …
claiming comments. This shared task comprises three binary classification subtasks with the …
KOLD: Korean offensive language dataset
Recent directions for offensive language detection are hierarchical modeling, identifying the
type and the target of offensive language, and interpretability with offensive span annotation …
type and the target of offensive language, and interpretability with offensive span annotation …
Findings of the Shared Task on Offensive Span Identification from Code-Mixed Tamil-English Comments
Offensive content moderation is vital in social media platforms to support healthy online
discussions. However, their prevalence in codemixed Dravidian languages is limited to …
discussions. However, their prevalence in codemixed Dravidian languages is limited to …
SOLID: A large-scale semi-supervised dataset for offensive language identification
The widespread use of offensive content in social media has led to an abundance of
research in detecting language such as hate speech, cyberbullying, and cyber-aggression …
research in detecting language such as hate speech, cyberbullying, and cyber-aggression …
GenEx: A Commonsense-aware Unified Generative Framework for Explainable Cyberbullying Detection
With the rise of social media and online communication, the issue of cyberbullying has
gained significant prominence. While extensive research is being conducted to develop …
gained significant prominence. While extensive research is being conducted to develop …
SOLD: Sinhala offensive language dataset
The widespread of offensive content online, such as hate speech and cyber-bullying, is a
global phenomenon. This has sparked interest in the artificial intelligence (AI) and natural …
global phenomenon. This has sparked interest in the artificial intelligence (AI) and natural …