Comparison between machine learning and deep learning approaches for the detection of toxic comments on social networks
A Bonetti, M Martínez-Sober, JC Torres, JM Vega… - Applied Sciences, 2023 - mdpi.com
The way we communicate has been revolutionised by the widespread use of social
networks. Any kind of online message can reach anyone in the world almost instantly. The …
networks. Any kind of online message can reach anyone in the world almost instantly. The …
Comparison of deep learning models and various text pre-processing techniques for the toxic comments classification
The emergence of anti-social behaviour in online environments presents a serious issue in
today's society. Automatic detection and identification of such behaviour are becoming …
today's society. Automatic detection and identification of such behaviour are becoming …
Addressing unintended bias in toxicity detection: An lstm and attention-based approach
In the digital era, online platforms serve as crucial hubs for social interactions and idea
exchange. However, these platforms are continually shadowed by toxic comments that …
exchange. However, these platforms are continually shadowed by toxic comments that …
Why should adversarial perturbations be imperceptible? rethink the research paradigm in adversarial nlp
Textual adversarial samples play important roles in multiple subfields of NLP research,
including security, evaluation, explainability, and data augmentation. However, most work …
including security, evaluation, explainability, and data augmentation. However, most work …
A Taxonomy of Rater Disagreements: Surveying Challenges & Opportunities from the Perspective of Annotating Online Toxicity
Toxicity is an increasingly common and severe issue in online spaces. Consequently, a rich
line of machine learning research over the past decade has focused on computationally …
line of machine learning research over the past decade has focused on computationally …
[HTML][HTML] Toxicity detection in online Georgian discussions
N Lashkarashvili, M Tsintsadze - International Journal of Information …, 2022 - Elsevier
Online social platforms have become omnipresent. While these environments are beneficial
for sharing messages, ideas, or information of any kind, they also expose cyber-bullying …
for sharing messages, ideas, or information of any kind, they also expose cyber-bullying …
Use of data augmentation techniques in detection of antisocial behavior using deep learning methods
The work presented in this paper focuses on the use of data augmentation techniques
applied in the domain of the detection of antisocial behavior. Data augmentation is a …
applied in the domain of the detection of antisocial behavior. Data augmentation is a …
Toxic Fake News Detection and Classification for Combating COVID-19 Misinformation
The emergence of COVID-19 has led to a surge in fake news on social media, with toxic fake
news having adverse effects on individuals, society, and governments. Detecting toxic fake …
news having adverse effects on individuals, society, and governments. Detecting toxic fake …
Technology acceptance and transparency demands for toxic language classification–interviews with moderators of public online discussion fora
Many online discussion providers consider using algorithm-based moderation software to
support their employees in moderating toxic communication. Such technology is also …
support their employees in moderating toxic communication. Such technology is also …
Toxic comment classification using hybrid deep learning model
R Beniwal, A Maurya - … networks and application: Proceedings of ICSCN …, 2021 - Springer
With the increasing availability of affordable data services and social media presence, our
life is not untouched with 'cyber,'ie, electronic technology. With it, various challenges and …
life is not untouched with 'cyber,'ie, electronic technology. With it, various challenges and …