Unveiling Sentiment Nuances: Comparative Study on Aspect Based Sentiment Analysis Approaches

Aspect based sentiments analysis address the limitation of coarse grained sentiments analysis by providing opinion for specific aspect of entities. A comprehensive review is presented in this paper to review NLP technique to for text processing, classification model for aspect term identification, sentiment polarity detection, and opinion expression classification. Technological advances in neural network based model, specifically transformer-based model have significantly enhanced contextual understanding in ABSA tasks. The paper also shed the light on challenges such as domain adaptation, multilingual limitations, cultural sentiment variation, data sparsity, and computational in-efficiencies. A comparative analysis of ABSA applications across domains including politics ,tourism, healthcare and education is provided. The study concludes with a future roadmap emphasizing scalable models, cultural adaptability, and explainable AI techniques, offering valuable insights for researchers and practitioners.