التفاصيل البيبلوغرافية
| العنوان: |
Leverage Fusion of Sentiment Features and Bert-based Approach to Improve Hate Speech Detection |
| المؤلفون: |
Cheng, Kai Hsiang |
| المساهمون: |
Computer Science, Lu, Chang Tien, Chen, Ing Ray, Cho, Jin-Hee |
| بيانات النشر: |
Virginia Tech |
| سنة النشر: |
2022 |
| المجموعة: |
VTechWorks (VirginiaTech) |
| مصطلحات موضوعية: |
hate speech detection, sentiment features, BERT |
| الوصف: |
Social media has become an important place for modern people to conveniently share and exchange their ideas and opinions. However, not all content on the social media have positive impact. Hate speech is one kind of harmful content that people use abusive speech attacking or promoting hate towards a specific group or an individual. With online hate speech on the rise these day, people have explored ways to automatically recognize the hate speech, and among the ways people have studied, the Bert-based approach is promising and thus dominates SemEval-2019 Task 6, a hate speech detection competition. In this work, the method of fusion of sentiment features and Bert-based approach is proposed. The classic Bert architecture for hate speech detection is modified to fuse with additional sentiment features, provided by an extractor pre-trained on Sentiment140. The proposed model is compared with top-3 models in SemEval-2019 Task 6 Subtask A and achieves 83.1% F1 score that better than the models in the competition. Also, to see if additional sentiment features benefit the detectoin of hate speech, the features are fused with three kind of deep learning architectures respectively. The results show that the models with sentiment features perform better than those models without sentiment features. ; Master of Science ; Social media has become an important place for modern people to conveniently share and exchange their ideas and opinions. However, not all content on the social media have positive impact. Hate speech is one kind of harmful content that people use abusive speech attacking or promoting hate towards a specific group or an individual. With online hate speech on the rise these day, people have explored ways to automatically recognize the hate speech, and among the ways people have studied, Bert is one of promising approach for automatic hate speech recognition. Bert is a kind of deep learning model for natural language processing (NLP) that originated from Transformer developed by Google in 2017. The Bert has ... |
| نوع الوثيقة: |
thesis |
| وصف الملف: |
ETD; application/pdf |
| اللغة: |
English |
| العلاقة: |
vt_gsexam:35115; http://hdl.handle.net/10919/110929Test |
| الإتاحة: |
http://hdl.handle.net/10919/110929Test |
| حقوق: |
In Copyright ; http://rightsstatements.org/vocab/InC/1.0Test/ |
| رقم الانضمام: |
edsbas.1125F341 |
| قاعدة البيانات: |
BASE |
