Document Type
Dissertation
Disciplines
1.2 COMPUTER AND INFORMATION SCIENCE, Computer Sciences
Abstract
Hate speech can be defined as forms of expression that incite hatred or encourage violence towards a person or group based on race, religion, gender, or sexual orientation. Hate speech has gravitated towards social media as its primary platform, and its propagation represents profound risks to both the mental well-being and physical safety of targeted groups. Countermeasures to moderate hate speech face challenges due to the volumes of data generated in social media, leading companies, and the research community to evaluate methods to automate its detection. The emergence of BERT and other pre-trained transformer-based models for transfer learning in the Natural Language Processing (NLP) domain has enabled state-of-theart performance in hate speech detection. Yet, there are concerns around the performance at scale and environmental costs of increasingly large models.
Recommended Citation
mcGowran, A. (2022). Evaluating the Performance Impact of Fine-Tuning Optimization Strategies on Pre-Trained DistilBERT Models Towards Hate Speech Detection in Social Media. [Technological University Dublin].
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Publication Details
A dissertation submitted in partial fulfilment of the requirements of Technological University Dublin for the degree of M.Sc. in Computer Science (Data Analytics) April 03, 2022.