A review of text style transfer using deep learning

M Toshevska, S Gievska - IEEE Transactions on Artificial …, 2021 - ieeexplore.ieee.org
Style is an integral component of a sentence indicated by the choice of words a person
makes. Different people have different ways of expressing themselves; however, they adjust …

[HTML][HTML] Offensive, aggressive, and hate speech analysis: From data-centric to human-centered approach

J Kocoń, A Figas, M Gruza, D Puchalska… - Information Processing …, 2021 - Elsevier
Abstract Analysis of subjective texts like offensive content or hate speech is a great
challenge, especially regarding annotation process. Most of current annotation procedures …

Impact of politically biased data on hate speech classification

M Wich, J Bauer, G Groh - Proceedings of the fourth workshop on …, 2020 - aclanthology.org
One challenge that social media platforms are facing nowadays is hate speech. Hence,
automatic hate speech detection has been increasingly researched in recent years-in …

Multi-contextual learning in disinformation research: A review of challenges, approaches, and opportunities

B Das - Online Social Networks and Media, 2023 - Elsevier
Though a fair amount of research is being done to address disinformation in online social
media, it has so far managed to stay ahead of the researchers' learning curves forcing the …

Understanding and interpreting the impact of user context in hate speech detection

E Mosca, M Wich, G Groh - … of the Ninth International Workshop on …, 2021 - aclanthology.org
As hate speech spreads on social media and online communities, research continues to
work on its automatic detection. Recently, recognition performance has been increasing …

Offensive language identification in low-resourced code-mixed dravidian languages using pseudo-labeling

A Hande, K Puranik, K Yasaswini… - arxiv preprint arxiv …, 2021 - arxiv.org
Social media has effectively become the prime hub of communication and digital marketing.
As these platforms enable the free manifestation of thoughts and facts in text, images and …

Automatic identification of harmful, aggressive, abusive, and offensive language on the web: A survey of technical biases informed by psychology literature

A Balayn, J Yang, Z Szlavik, A Bozzon - ACM Transactions on Social …, 2021 - dl.acm.org
The automatic detection of conflictual languages (harmful, aggressive, abusive, and
offensive languages) is essential to provide a healthy conversation environment on the Web …

[PDF][PDF] Benchmarking post-hoc interpretability approaches for transformer-based misogyny detection

G Attanasio, D Nozza, E Pastor… - Proceedings of NLP …, 2022 - iris.unibocconi.it
Warning: This paper contains examples of language that some people may find offensive.
Transformer-based Natural Language Processing models have become the standard for …

Multimodal deep learning with discriminant descriptors for offensive memes detection

A Alzu'bi, L Bani Younis, A Abuarqoub… - ACM Journal of Data …, 2023 - dl.acm.org
A meme is a visual representation that illustrates a thought or concept. Memes are
spreading steadily among people in this era of rapidly expanding social media platforms …

JudithJeyafreeda@ LT-EDI-2023: Using GPT model for recognition of Homophobia/Transphobia detection from social media

JJ Andrew - Proceedings of the Third Workshop on Language …, 2023 - aclanthology.org
Homophobia and Transphobia is defined as hatred or discomfort towards Gay, Lesbian,
Transgender or Bisexual people. With the increase in social media, communication has …