Bias Mitigation in Mental Health Sentiment Analysis Models Using BERT with Fairness Techniques

1. Introduction 1.1 Research Background 1.2 Problem Statement 1.3 Research Objectives 1.4 Thesis Structure 2. Literature Review 2.1 Sentiment Analysis in Mental Health 2.2 Bias in Machine Learning Models 2.3 Introduction to BERT 2.4 Fairness Techniques Overview 3. Methodology 3.1 Data Collection and Preprocessing 3.2 Implementation of BERT 3.3 Fairness Technique Application 3.4 Evaluation Metrics 4. Bias Identification 4.1 Types of Bias in Sentiment Analysis 4.2 Identifying Bias in BERT Models 4.3 Bias Measurement Techniques 5. Bias Mitigation Techniques 5.1 Pre-processing Methods 5.2 In-processing Techniques 5.3 Post-processing Approaches 6. Experimental Setup 6.1 Dataset Description 6.2 Tools and Frameworks Used 6.3 Experiment Design 7. Results and Discussion 7.1 Quantitative Results 7.2 Qualitative Analysis 7.3 Comparison with Existing Methods 8. Conclusion and Future Work 8.1 Summary of Findings 8.2 Implications of the Study 8.3 Limitations and Challenges 8.4 Suggestions for Future Research