[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 …

Overview of the hasoc subtrack at fire 2021: Hate speech and offensive content identification in english and indo-aryan languages and conversational hate speech

S Modha, T Mandl, GK Shahi, H Madhu… - Proceedings of the 13th …, 2021 - dl.acm.org
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 …

Detecting offensive speech in conversational code-mixed dialogue on social media: A contextual dataset and benchmark experiments

H Madhu, S Satapara, S Modha, T Mandl… - Expert Systems with …, 2023 - Elsevier
Abstract The spread of Hate Speech on online platforms is a severe issue for societies and
requires the identification of offensive content by platforms. Research has modeled Hate …

Hate speech detection in social media: Techniques, recent trends, and future challenges

A Rawat, S Kumar, SS Samant - Wiley Interdisciplinary Reviews …, 2024 - Wiley Online Library
Abstract The realm of Natural Language Processing and Text Mining has seen a surge in
interest from researchers in hate speech detection, leading to an increase in related studies …

EnsMulHateCyb: Multilingual hate speech and cyberbully detection in online social media

E Mahajan, H Mahajan, S Kumar - Expert Systems with Applications, 2024 - Elsevier
Nowadays, users across the globe interact with one another for information exchange,
communication, and association on various online social media. However, some individuals …

Overview of the hasoc subtrack at fire 2021: Hate speech and offensive content identification in english and indo-aryan languages

T Mandl, S Modha, GK Shahi, H Madhu… - arxiv preprint arxiv …, 2021 - arxiv.org
The widespread of offensive content online such as hate speech poses a growing societal
problem. AI tools are necessary for supporting the moderation process at online platforms …

A transfer learning approach for detecting offensive and hate speech on social media platforms

I Priyadarshini, S Sahu, R Kumar - Multimedia Tools and Applications, 2023 - Springer
Over the last few decades, the expansion of technology and the internet has led to the
number of users proliferating on social media, with a simultaneous increase in hate speech …

Fuser: An enhanced multimodal fusion framework with congruent reinforced perceptron for hateful memes detection

F Wu, B Gao, X Pan, L Li, Y Ma, S Liu, Z Liu - Information Processing & …, 2024 - Elsevier
As a multimodal form of hate speech on social media, hateful memes are more aggressive
and cryptic threats to the real life of humans. Automatic detection of hateful memes is crucial …

Learning interpretable word embeddings via bidirectional alignment of dimensions with semantic concepts

LK Şenel, F Şahinuç, V Yücesoy, H Schütze… - Information Processing …, 2022 - Elsevier
We propose bidirectional imparting or BiImp, a generalized method for aligning embedding
dimensions with concepts during the embedding learning phase. While preserving the …

RETRACTED ARTICLE: Multilingual hate speech detection sentimental analysis on social media platforms using optimal feature extraction and hybrid diagonal gated …

P Kar, S Debbarma - The Journal of Supercomputing, 2023 - Springer
Many activities are conducted on social media platforms, such as promoting products,
sharing news and sharing achievements. As a result of users' freedom and anonymity on …