Lexicon Based

Lexicon-based methods utilize pre-defined dictionaries of words and their associated sentiment or meaning to analyze text, offering interpretability and speed advantages over complex machine learning models. Current research explores integrating lexicons with transformer-based models and large language models to improve performance on tasks like sentiment analysis, depression symptom estimation, and low-resource language processing, often comparing their effectiveness against machine learning and deep learning alternatives. This approach is significant for its potential to enhance the efficiency and explainability of natural language processing tasks, particularly in resource-constrained settings and applications requiring transparent decision-making.