A review on abusive content automatic detection: approaches, challenges and opportunities
B Alrashidi, A Jamal, I Khan, A Alkhathlan - PeerJ Computer Science, 2022 - peerj.com
The increasing use of social media has led to the emergence of a new challenge in the form
of abusive content. There are many forms of abusive content such as hate speech …
of abusive content. There are many forms of abusive content such as hate speech …
Identifying hot topic trends in streaming text data using sequential evolution model based on distributed representations
Hot topic trends have become increasingly important in the era of social media, as these
trends can spread rapidly through online platforms and significantly impact public discourse …
trends can spread rapidly through online platforms and significantly impact public discourse …
[HTML][HTML] Deep learning-based approaches for abusive content detection and classification for multi-class online user-generated data
With the rapid growth of social media culture, the use of offensive or hateful language has
surged, which necessitates the development of effective abusive language detection models …
surged, which necessitates the development of effective abusive language detection models …
State-of-the-art in Open-domain Conversational AI: A Survey
We survey SoTA open-domain conversational AI models with the objective of presenting the
prevailing challenges that still exist to spur future research. In addition, we provide statistics …
prevailing challenges that still exist to spur future research. In addition, we provide statistics …
T5 for Hate Speech, Augmented Data, and Ensemble
We conduct relatively extensive investigations of automatic hate speech (HS) detection
using different State-of-The-Art (SoTA) baselines across 11 subtasks spanning six different …
using different State-of-The-Art (SoTA) baselines across 11 subtasks spanning six different …
[PDF][PDF] A text-to-text model for multilingual offensive language identification
T Ranasinghe, M Zampieri - Findings of the Association for …, 2023 - aclanthology.org
The ubiquity of offensive content on social media is a growing cause for concern among
companies and government organizations. Recently, transformer-based models such as …
companies and government organizations. Recently, transformer-based models such as …
Vector representations of idioms in conversational systems
In this study, we demonstrate that an open-domain conversational system trained on idioms
or figurative language generates more fitting responses to prompts containing idioms …
or figurative language generates more fitting responses to prompts containing idioms …
NLP-LTU at SemEval-2023 Task 10: The Impact of Data Augmentation and Semi-Supervised Learning Techniques on Text Classification Performance on an …
In this paper, we propose a methodology for task 10 of SemEval23, focusing on detecting
and classifying online sexism in social media posts. The task is tackling a serious issue, as …
and classifying online sexism in social media posts. The task is tackling a serious issue, as …
Leveraging sentiment data for the detection of homophobic/transphobic content in a multi-task, multi-lingual setting using transformers
Hateful content is published and spread on social media at an increasing rate, harming the
user experience. In addition, hateful content targeting particular, marginalized/vulnerable …
user experience. In addition, hateful content targeting particular, marginalized/vulnerable …
Vector representations of idioms in data-driven chatbots for robust assistance
O Adewumi - 2022 - diva-portal.org
This thesis presents resources capable of enhancing solutions of some Natural Language
Processing (NLP) tasks, demonstrates the learning of abstractions by deep models through …
Processing (NLP) tasks, demonstrates the learning of abstractions by deep models through …