[HTML][HTML] A survey on hate speech detection and sentiment analysis using machine learning and deep learning models

M Subramanian, VE Sathiskumar… - Alexandria Engineering …, 2023 - Elsevier
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 …

Hate speech detection: A comprehensive review of recent works

A Gandhi, P Ahir, K Adhvaryu, P Shah… - Expert …, 2024 - Wiley Online Library
There has been surge in the usage of Internet as well as social media platforms which has
led to rise in online hate speech targeted on individual or group. In the recent years, hate …

COLD: A benchmark for Chinese offensive language detection

J Deng, J Zhou, H Sun, C Zheng, F Mi, H Meng… - arXiv preprint arXiv …, 2022 - arxiv.org
Offensive language detection is increasingly crucial for maintaining a civilized social media
platform and deploying pre-trained language models. However, this task in Chinese is still …

[HTML][HTML] Recognizing misogynous memes: Biased models and tricky archetypes

G Rizzi, F Gasparini, A Saibene, P Rosso… - Information Processing & …, 2023 - Elsevier
Warning: This paper contains examples of language and images which may be offensive.
Misogyny is a form of hate against women and has been spreading exponentially through …

[PDF][PDF] Overview of the multilingual text detoxification task at pan 2024

D Dementieva, D Moskovskiy, N Babakov… - Working Notes of …, 2024 - ceur-ws.org
Despite different countries and social platform regulations, digital abusive speech persists
as a significant challenge. One of the way to tackle abusive, or more specifically, toxic …

Rethinking Machine Ethics--Can LLMs Perform Moral Reasoning through the Lens of Moral Theories?

J Zhou, M Hu, J Li, X Zhang, X Wu, I King… - arXiv preprint arXiv …, 2023 - arxiv.org
Making moral judgments is an essential step toward developing ethical AI systems.
Prevalent approaches are mostly implemented in a bottom-up manner, which uses a large …

Quantifying controversy from stance, sentiment, offensiveness and sarcasm: a fine-grained controversy intensity measurement framework on a Chinese dataset

H Wang, Y Wang, X Song, B Zhou, X Zhao, F Xie - World Wide Web, 2023 - Springer
Controversy measurement on social media plays an important part in understanding public
opinion. Various topics are frequently hotly debated on social media platforms including …

Detecting hateful and offensive speech in Arabic social media using transfer learning

Z Boulouard, M Ouaissa, M Ouaissa, M Krichen… - Applied Sciences, 2022 - mdpi.com
The democratization of access to internet and social media has given an opportunity for
every individual to openly express his or her ideas and feelings. Unfortunately, this has also …

Multihateclip: A multilingual benchmark dataset for hateful video detection on youtube and bilibili

H Wang, TR Yang, U Naseem, RKW Lee - Proceedings of the 32nd ACM …, 2024 - dl.acm.org
Hate speech is a pressing issue in modern society, with significant effects both online and
offline. Recent research in hate speech detection has primarily centered on text-based …

Leveraging posts' and authors' metadata to spot several forms of abusive comments in twitter

M Casavantes, ME Aragón, LC González… - Journal of Intelligent …, 2023 - Springer
Social media is frequently plagued with undesirable phenomena such as cyberbullying and
abusive content in the form of hateful and racist posts. Therefore, it is crucial to study and …