1 INTRODUCTION  
2 BACKGROUND: FOUNDATIONS, GOALS, AND APPLICATIONS OF DATA AUGMENTATION  
3 TEXTUAL DATA AUGMENTATION METHODS  
3.1 Data Space  
3.2 Feature Space  
3.3 Combination of Augmentation Methods  
3.4 Training Strategies  
3.5 Filtering Mechanisms  
4 DISCUSSION: A RESEARCH AGENDA FOR TEXTUAL DATA AUGMENTATION  
4.1 Researching the Merits of Data Augmentation in the Light of Large Pre-trained Language Models  
4.2 Improving Existing Data Augmentation Approaches  
4.3 Establishing more Comprehensive Evaluation Criteria and Standards for Method Comparison  
4.4 Enhancing the Understanding of Text Data Augmentation  
4.5 Fostering the Usability of Data Augmentation Application  
5 CONCLUSION