[HTML][HTML] A systematic review of hate speech automatic detection using natural language processing
With the multiplication of social media platforms, which offer anonymity, easy access and
online community formation and online debate, the issue of hate speech detection and …
online community formation and online debate, the issue of hate speech detection and …
A survey on bert and its applications
A recently developed language representation model named Bidirectional Encoder
Representation from Transformers (BERT) is based on an advanced trained deep learning …
Representation from Transformers (BERT) is based on an advanced trained deep learning …
Time of your hate: The challenge of time in hate speech detection on social media
The availability of large annotated corpora from social media and the development of
powerful classification approaches have contributed in an unprecedented way to tackle the …
powerful classification approaches have contributed in an unprecedented way to tackle the …
Cross-lingual few-shot learning on unseen languages
Large pre-trained language models (LMs) have demonstrated the ability to obtain good
performance on downstream tasks with limited examples in cross-lingual settings. However …
performance on downstream tasks with limited examples in cross-lingual settings. However …
Hate speech in a telegram conspiracy channel during the first year of the COVID-19 pandemic
Research has explored how the COVID-19 pandemic triggered a wave of conspiratorial
thinking and online hate speech, but little is empirically known about how different phases of …
thinking and online hate speech, but little is empirically known about how different phases of …
Detecting racial stereotypes: An Italian social media corpus where psychology meets NLP
The generation of stereotypes allows us to simplify the cognitive complexity we have to deal
with in everyday life. Stereotypes are extensively used to describe people who belong to a …
with in everyday life. Stereotypes are extensively used to describe people who belong to a …
A hybrid lexicon-based and neural approach for explainable polarity detection
In this work, we propose BERT-WMAL, a hybrid model that brings together information
coming from data through the recent transformer deep learning model and those obtained …
coming from data through the recent transformer deep learning model and those obtained …
Deep-learning-based natural-language-processing models to identify cardiovascular disease hospitalisations of patients with diabetes from routine visits' text
Writing notes is the most widespread method to report clinical events. Therefore, most of the
information about the disease history of a patient remains locked behind free-form text …
information about the disease history of a patient remains locked behind free-form text …
Please note that I'm just an AI: Analysis of behavior patterns of LLMs in (non-) offensive speech identification
Offensive speech is highly prevalent on online platforms. Being trained on online data,
Large Language Models (LLMs) display undesirable behaviors, such as generating harmful …
Large Language Models (LLMs) display undesirable behaviors, such as generating harmful …
Advancing content moderation: Evaluating large language models for detecting sensitive content across text, images, and videos
The widespread dissemination of hate speech, harassment, harmful and sexual content, and
violence across websites and media platforms presents substantial challenges and …
violence across websites and media platforms presents substantial challenges and …