Hate speech detection in social media: Techniques, recent trends, and future challenges
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 …
interest from researchers in hate speech detection, leading to an increase in related studies …
A deep learning-based framework for offensive text detection in unstructured data for heterogeneous social media
Social media such as Facebook, Instagram, and Twitter are powerful and essential platforms
where people express and share their ideas, knowledge, talents, and abilities with others …
where people express and share their ideas, knowledge, talents, and abilities with others …
Enhancing the fairness of offensive memes detection models by mitigating unintended political bias
This paper tackles the critical challenge of detecting and mitigating unintended political bias
in offensive meme detection. Political memes are a powerful tool that can be used to …
in offensive meme detection. Political memes are a powerful tool that can be used to …
A transformer-based generative adversarial learning to detect sarcasm from Bengali text with correct classification of confusing text
Sarcasm detection research in Bengali is still limited due to a lack of relevant resources. In
this context, getting high-quality annotated data is costly and time-consuming. Therefore, in …
this context, getting high-quality annotated data is costly and time-consuming. Therefore, in …
A Multimodal Framework to Detect Target Aware Aggression in Memes
Internet memes have gained immense traction as a medium for individuals to convey
emotions, thoughts, and perspectives on social media. While memes often serve as sources …
emotions, thoughts, and perspectives on social media. While memes often serve as sources …
A Deep-Learning Based Approach for Multi-class Cyberbullying Classification Using Social Media Text and Image Data
I Tabassum, V Nunavath - Norsk IKT-konferanse for forskning og utdanning, 2024 - ntnu.no
Social media sites like Facebook, Instagram, Twitter, LinkedIn, have become crucial for
content creation and distribution, influencing business, politics, and personal relationships …
content creation and distribution, influencing business, politics, and personal relationships …
Align before Attend: Aligning Visual and Textual Features for Multimodal Hateful Content Detection
Multimodal hateful content detection is a challenging task that requires complex reasoning
across visual and textual modalities. Therefore, creating a meaningful multimodal …
across visual and textual modalities. Therefore, creating a meaningful multimodal …
Mu2STS: A Multitask Multimodal Sarcasm-Humor-Differential Teacher-Student Model for Sarcastic Meme Detection
Memes, a prevalent form of online communication, often express opinions, emotions, and
creativity concisely and entertainingly. Amidst the diverse landscape of memes, the realm of …
creativity concisely and entertainingly. Amidst the diverse landscape of memes, the realm of …
Toxic Memes: A Survey of Computational Perspectives on the Detection and Explanation of Meme Toxicities
DSM Pandiani, ETK Sang, D Ceolin - arXiv preprint arXiv:2406.07353, 2024 - arxiv.org
Internet memes, channels for humor, social commentary, and cultural expression, are
increasingly used to spread toxic messages. Studies on the computational analyses of toxic …
increasingly used to spread toxic messages. Studies on the computational analyses of toxic …
Enhancing Offensive Bengali Social Media Meme Detection: A Weighted Ensemble Architecture for Predicting Type and Target Classes
This paper investigates the classification of offensive memes using a weighted ensemble
approach of multimodal models that integrates visual and textual information. A meticulously …
approach of multimodal models that integrates visual and textual information. A meticulously …