MBTI Augmented Dataset

This dataset extends the standard Myers-Briggs Type Indicator (MBTI) dataset, widely available on Kaggle, by incorporating advanced data augmentation techniques leveraging GPT-based Transformers. The augmentation addresses inherent class imbalance and data sparsity issues in the original dataset, significantly enriching the volume and diversity of textual samples while maintaining linguistic and contextual fidelity to the MBTI personality types.

The dataset contains augmented textual data for all 16 personality types, ensuring an even distribution across classes to facilitate robust training of machine learning and deep learning models. The augmentation process employs GPT Transformers to generate synthetic text samples based on the linguistic characteristics and behavioral patterns inherent to each personality type. This approach ensures the preservation of semantic coherence and alignment with the psychological traits described by the MBTI framework.

The dataset is structured to support both classification and natural language processing tasks, making it an ideal resource for researchers exploring personality prediction, text generation, or related domains. It includes detailed metadata documenting the augmentation process, including parameters and techniques used for generating synthetic samples. By addressing key limitations of the original dataset, this enhanced dataset aims to advance research in personality recognition and text-based psychological analysis.